pharmaccess.bib

@misc{2021leveraging,
  title = {Leveraging the {{OpenHIM}} \& {{Instant OpenHIE}} to {{Support COVID-19 Data Exchange}}},
  year = {2021},
  month = jul,
  journal = {Jembi Health Systems},
  urldate = {2023-06-06},
  abstract = {Jembi is proud to have completed work on developing a prototype solution supporting COVID-19 data exchange using the OpenHIM and Instant OpenHIE to support COVID-19 case reporting and lab result submission using the HL7 FHIR standard. Digital Square funded this work, and it was completed in collaboration with the OpenHIE COVID-19 task force, with support from IntelliSOFT. The objective of the project was to develop a generic COVID-19 data exchange solution that could be adapted to country needs,},
  howpublished = {https://www.jembi.org/post/leveraging-the-openhim-instant-openhie-to-support-covid-19-data-exchange},
  langid = {english},
  file = {/Users/dkapitan/Zotero/storage/Z7NSEGRL/leveraging-the-openhim-instant-openhie-to-support-covid-19-data-exchange.html}
}

@techreport{2023african,
  title = {African {{Union Health Information Exchange Guidelines}} and {{Standards}}},
  year = {2023},
  month = mar,
  institution = {African Union},
  urldate = {2024-01-10},
  abstract = {Preface The application of digital health technology is growing at a rapid rate in Africa, with the goals of improving the delivery of healthcare services and more effectively reaching out to remote and underserved communities. The lack of enabling guidelines and standards across the continent, on the other hand, makes it difficult to share data [{\dots}]},
  langid = {british},
  file = {/Users/dkapitan/Zotero/storage/P2RNIMZR/African Union Health Information Exchange Guidelin.pdf;/Users/dkapitan/Zotero/storage/5A9LBBLH/african-union-health-information-exchange-guidelines-and-standards.html}
}

@misc{2023hcx,
  title = {{{HCX Protocol}} v0.9},
  year = {2023},
  month = dec,
  urldate = {2024-01-18},
  abstract = {Open-source, community driven protocol for Health Claims data Exchange},
  langid = {english},
  file = {/Users/dkapitan/Zotero/storage/7R9WM4UH/hcxprotocol.io.html}
}

@misc{2023healthcare,
  title = {Healthcare {{Exchange Standards}}: {{Transitioning Federated HIE}} from {{XCA}} to {{FHIR Query}}},
  shorttitle = {Healthcare {{Exchange Standards}}},
  year = {2023},
  month = mar,
  journal = {Healthcare Exchange Standards},
  urldate = {2024-08-20},
  file = {/Users/dkapitan/Zotero/storage/9NIHVKGS/transitioning-federated-hie-from-xca-to.html}
}

@article{abbas2021business,
  title = {Business {{Data Sharing}} through {{Data Marketplaces}}: {{A Systematic Literature Review}}},
  shorttitle = {Business {{Data Sharing}} through {{Data Marketplaces}}},
  author = {Abbas, Antragama Ewa and Agahari, Wirawan and van de Ven, Montijn and Zuiderwijk, Anneke and de Reuver, Mark},
  year = {2021},
  month = jan,
  journal = {BLED 2021 Proceedings},
  file = {/Users/dkapitan/Zotero/storage/NS4TWGF4/13.html}
}

@article{abbasian2023phas,
  title = {{{PHAS}}: {{An End-to-End}}, {{Open-Source}}, and {{Portable Healthcare Analytics Stack}}},
  shorttitle = {{{PHAS}}},
  author = {Abbasian, Mahyar and Khatibi, Elahe and Azimi, Iman and Rahmani, Amir M.},
  year = {2023},
  month = jan,
  journal = {Procedia Computer Science},
  series = {The 14th {{International Conference}} on {{Ambient Systems}}, {{Networks}} and {{Technologies Networks}} ({{ANT}}) and {{The}} 6th {{International Conference}} on {{Emerging Data}} and {{Industry}} 4.0 ({{EDI40}})},
  volume = {220},
  pages = {511--518},
  issn = {1877-0509},
  doi = {10.1016/j.procs.2023.03.065},
  urldate = {2024-02-05},
  abstract = {In today's binary world, digital health is of paramount importance, primarily due to the prevalence of IoT devices, upsurging health costs, growing elderly population, and shortage of clinical providers, to name a few. In light of these, providing efficient and smarter full-stack healthcare data analytics to manage and process healthcare data is a crucial topic from both academic and professional perspectives. The key goals of this full-stack healthcare data analytics are to detect health issues and promote human-being health proactively. The existing healthcare data analytics stacks are generally classified into commercial or open-source solutions. In designing a healthcare data stack, it is critical to offer the researchers a collaborative, modular, easy-to-use, cost/time-effective, reproducible, uniform, and shared- knowledge framework. Such healthcare stacks need to pave the way for researchers to focus on developing data analytics algorithms, and the underlying infrastructure should comply with longitudinal characteristics of healthcare data. Nonetheless, the existing healthcare data analytics stacks need holistically incorporate all the parameters mentioned. In this paper, we propose a novel healthcare data analytics stack called Open-Source Portable Healthcare Analytics Stack (PHAS) to address this issue. PHAS considers the mentioned features by fusing the merits of open-source and commercial solutions at the right place in its architecture. PHAS proposes a new shared-knowledge and time-series-aware framework, which enables researchers to perform health data collection, integration, storage, visualization, and analysis. Moreover, we demonstrate the capabilities of the PHAS framework by implementing an anomaly detection algorithm for heart rate and blood pressure anomaly detection using the Medical Information Mart for Intensive Care III (MIMIC III) dataset. We provide open-source PHAS for the community to integrate into their solutions.},
  keywords = {Data Analytics Stack,Framework,Healthcare,Machine Learning},
  file = {/Users/dkapitan/Zotero/storage/HV696HQC/Abbasian et al. - 2023 - PHAS An End-to-End, Open-Source, and Portable Hea.pdf;/Users/dkapitan/Zotero/storage/FDGKYXHS/S1877050923006002.html}
}

@article{adler-milstein2021survey,
  title = {A {{Survey Of Health Information Exchange Organizations In Advance Of A Nationwide Connectivity Framework}}},
  author = {{Adler-Milstein}, Julia and Garg, Anjali and Zhao, Wendi and Patel, Vaishali},
  year = {2021},
  month = may,
  journal = {Health Affairs},
  volume = {40},
  number = {5},
  pages = {736--744},
  publisher = {Health Affairs},
  issn = {0278-2715},
  doi = {10.1377/hlthaff.2020.01497},
  urldate = {2024-08-20},
  abstract = {After more than a decade of investment in electronic health information exchange (HIE), the Office of the National Coordinator for Health Information Technology is advancing a national framework---the Trusted Exchange Framework and Common Agreement---to connect islands of electronic data sharing. This national framework creates new potential opportunities and challenges for state and local health information organizations (HIOs). We undertook our sixth national HIO survey to assess the current state of HIOs and to newly examine anticipated responses to the Trusted Exchange Framework and Common Agreement. We identified eighty-nine operational HIOs, down from 106 in 2014. Although more than half of HIOs struggled with financial viability and competition from health information technology vendor--based HIE networks, many are large in scale, offer a breadth of services to diverse participants, and engage in network-to-network connectivity. Looking ahead, 56~percent of HIOs planned to participate in the Trusted Exchange Framework and Common Agreement, and 41~percent were unsure. As the Trusted Exchange Framework and Common Agreement advances basic network-to-network connectivity, HIOs that have experience with such connectivity while also offering value-added services will be well positioned for sustainability and growth.},
  file = {/Users/dkapitan/Zotero/storage/M4FGXBNQ/Adler-Milstein et al. - 2021 - A Survey Of Health Information Exchange Organizati.pdf}
}

@misc{aidbox,
  title = {Aidbox},
  author = {{Health Samurai}},
  year = {2024},
  urldate = {2024-01-18},
  howpublished = {https://docs.aidbox.app/storage-1/sql-on-fhir},
  langid = {english},
  file = {/Users/dkapitan/Zotero/storage/GE2IGNC9/sql-on-fhir.html}
}

@article{aiterrami2023spatial,
  title = {Spatial Big Data Architecture: {{From Data Warehouses}} and {{Data Lakes}} to the {{LakeHouse}}},
  shorttitle = {Spatial Big Data Architecture},
  author = {Ait Errami, Soukaina and Hajji, Hicham and Ait El Kadi, Kenza and Badir, Hassan},
  year = {2023},
  month = jun,
  journal = {Journal of Parallel and Distributed Computing},
  volume = {176},
  pages = {70--79},
  issn = {0743-7315},
  doi = {10.1016/j.jpdc.2023.02.007},
  urldate = {2023-04-23},
  abstract = {The construction of systems supporting spatial data has experienced great enthusiasm in the past, due to the richness of this type of data and their semantics, which can be used in the decision-making process in various fields. Thus, the problem of integrating spatial data into existing databases and information systems has been addressed by creating spatial extensions to relational tables or by creating spatial data warehouses, while arranging data structures and query languages by making them more spatially-aware. With the advent of Big Data, these conventional storage and spatial representation structures are becoming increasingly outdated, and required a new organization of spatial data. Approaches based on distributed storage and data lakes have been proposed, to integrate the complexity of spatial data, with operational and analytical systems which unfortunately quickly showed their limits. Recently the concept of lakehouse was introduced in order to integrate, among other things, the notion of reliability and ACID properties to the volume of data to be managed. This new data architecture is a combination of governed and reliable Data Warehouses and flexible, scalable and cost-effective Data Lakes. In this paper, we present how traditional approaches of spatial data management in the context of spatial big data have quickly shown their limits. We present a literature overview of these approaches, and how they led to the Data LakeHouse. We detail how the Lakehouse paradigm can be used and extended for managing spatial big data, by giving the different components and best practices for building a spatial data LakeHouse architecture optimized for the storage and computing over spatial big data.},
  langid = {english},
  keywords = {Data architecture,Data LakeHouse,Distributed systems,Spatial data,Storage},
  file = {/Users/dkapitan/Zotero/storage/PCEF375K/Ait Errami et al. - 2023 - Spatial big data architecture From Data Warehouse.pdf;/Users/dkapitan/Zotero/storage/W9QXW85X/errami2023spatial.pdf;/Users/dkapitan/Zotero/storage/R2F34LEV/S0743731523000229.html}
}

@article{akintunde2019health,
  title = {{{HEALTH INFORMATION EXCHANGE MODEL FOR NIGERIAN HEALTH INFORMATION SYSTEMS}}},
  author = {Akintunde, Oluwaseyi and Adebola, Akinsanya and Nzechukwu, Otuneme and Adetunji, Oluwatofunmi},
  year = {2019},
  month = feb,
  journal = {International Journal of Computer Science and Information Security,},
  volume = {17},
  pages = {181--203},
  abstract = {The advent and rapid proliferation of the internet has made information access and exchange more efficient and effective than it was before its invention. The internet permits data of various forms to be transmitted from entity to entity; this being an important feature of information age. The ability to take advantage of this technology to improve all aspects of human life and human endeavor is one of the keys to achieving sustainable growth and development for developing countries especially in terms of health care service delivery. The availability and accessibility of Health information whenever it is needed is important in determining the effectiveness of healthcare service delivery. This brings about the need for information exchange between different health information systems with reference to the Nigerian health sector i.e. an integrated system of interoperable health information systems that can exchange data in a meaningful and coherent way. The need for standardization is identified as major factor in achieving integration and interoperability between any groups of heterogeneous systems that must function together. This research work employed the review of related literature and existing health information exchange systems to determine the strengths and flaws of existing health information exchange systems and architectural models. How they can be adapted to and used to improve the Nigerian healthcare system was also a subject matter in this study. Based on the federated model of health information exchange; an architectural model and Framework was designed to demonstrate how interoperability can be achieved. Architectural models and Frameworks were designed to suit Nigeria's unique healthcare structure while supporting the designed architectural models with the development of an API using the federated model of health information exchange. Data was transferred between health information systems in JavaScript Object Notation (JSON) format using the developed API. The study concluded that the development of health information exchange Standards that conform to existing health information exchange reference models by the collaboration of medical and Information technology bodies in Nigeria would allow for a nationally integrated and interoperable health care system.},
  file = {/Users/dkapitan/Zotero/storage/6QVY4AK7/Akintunde et al. - 2019 - HEALTH INFORMATION EXCHANGE MODEL FOR NIGERIAN HEA.pdf}
}

@article{alaimo2022organizations,
  title = {Organizations {{Decentered}}: {{Data Objects}}, {{Technology}} and {{Knowledge}}},
  shorttitle = {Organizations {{Decentered}}},
  author = {Alaimo, Cristina and Kallinikos, Jannis},
  year = {2022},
  month = jan,
  journal = {Organization Science},
  volume = {33},
  number = {1},
  pages = {19--37},
  publisher = {INFORMS},
  issn = {1047-7039},
  doi = {10.1287/orsc.2021.1552},
  urldate = {2023-02-21},
  abstract = {Data are no longer simply a component of administrative and managerial work but a pervasive resource and medium through which organizations come to know and act upon the contingencies they confront. We theorize how the ongoing technological developments reinforce the traditional functions of data as instruments of management and control but also reframe and extend their role. By rendering data as technical entities, digital technologies transform the process of knowing and the knowledge functions data fulfil in socioeconomic life. These functions are most of the times mediated by putting together disperse and steadily updatable data in more stable entities we refer to as data objects. Users, customers, products, and physical machines rendered as data objects become the technical and cognitive means through which organizational knowledge, patterns, and practices develop. Such conditions loosen the dependence of data from domain knowledge, reorder the relative significance of internal versus external references in organizations, and contribute to a paradigmatic contemporary development that we identify with the decentering of organizations of which digital platforms are an important specimen.},
  keywords = {digital technology,digital transformation,information technology and systems,organization and management theory,organization communication and information systems,organizational form,organizational processes,practice},
  file = {/Users/dkapitan/Zotero/storage/CD76IHJ3/Alaimo and Kallinikos - 2022 - Organizations Decentered Data Objects, Technology.pdf}
}

@incollection{alunyu2023state,
  title = {State of {{Digital Health Communication Infrastructure}} in {{LMICs}}: {{Theory}}, {{Standards}} and {{Factors Affecting Their Implementation}}},
  shorttitle = {State of {{Digital Health Communication Infrastructure}} in {{LMICs}}},
  booktitle = {Current and {{Future Trends}} in {{Health}} and {{Medical Informatics}}},
  author = {Alunyu, Andrew Egwar and Amiyo, Mercy Rebekah and Nabukenya, Josephine},
  editor = {Daimi, Kevin and Alsadoon, Abeer and Seabra Dos Reis, Sara},
  year = {2023},
  series = {Studies in {{Computational Intelligence}}},
  pages = {109--134},
  publisher = {Springer Nature Switzerland},
  address = {Cham},
  doi = {10.1007/978-3-031-42112-9_6},
  urldate = {2024-03-08},
  abstract = {Healthcare data sharing is vital to the future of patient-centred care. However, it is challenged by weaknesses inherent in the communication infrastructure that support such data sharing. A key challenge has been pinned on the poor standardisation of digital health systems that make up the communication infrastructure thereby affecting the collection, processing, storage and transmission of health data/client's electronic medical records. This chapter presents experiences from Uganda regards progress in standardisation. A scoping literature review informed conceptualisation of digital health standardisation to involve setting standards context, standards development process, and implementation plus compliance monitoring. These three constructs guided the exploration of Uganda's state of digital health standardisation, conducted in four regions of the country. Whereas qualitative data collected were analysed using a thematic approach, the quantitative data was statistically analysed. Findings showed unstandardised implementations of digital health devices and applications, disparate and intermittent network connectivity with poor quality of service, limited digital health use skills, and inadequate facilitating resources. Further exploration attributed these limitations to weaknesses in the standardisation process and a lack of contextual standards to guide digital health implementations. Further works will develop a framework for fast-tracking the standardisation of the digital health communication infrastructure in low-resource health systems like Uganda.},
  isbn = {978-3-031-42112-9},
  langid = {english},
  keywords = {Communication infrastructure,Digital health,Healthcare data sharing,Standardisation framework,Standards},
  file = {/Users/dkapitan/Zotero/storage/AU2HC2IF/Alunyu et al. - 2023 - State of Digital Health Communication Infrastructu.pdf}
}

@article{amar2024electronic,
  title = {Electronic {{Health Record}} and {{Semantic Issues Using Fast Healthcare Interoperability Resources}}: {{Systematic Mapping Review}}},
  shorttitle = {Electronic {{Health Record}} and {{Semantic Issues Using Fast Healthcare Interoperability Resources}}},
  author = {Amar, Fouzia and April, Alain and Abran, Alain},
  year = {2024},
  month = jan,
  journal = {Journal of Medical Internet Research},
  volume = {26},
  number = {1},
  pages = {e45209},
  publisher = {JMIR Publications Inc., Toronto, Canada},
  doi = {10.2196/45209},
  urldate = {2024-02-05},
  abstract = {Background: The increasing use of electronic health records and the Internet of Things has led to interoperability issues at different levels (structural and semantic). Standards are important not only for successfully exchanging data but also for appropriately interpreting them (semantic interoperability). Thus, to facilitate the semantic interoperability of data exchanged in health care, considerable resources have been deployed to improve the quality of shared clinical data by structuring and mapping them to the Fast Healthcare Interoperability Resources (FHIR) standard. Objective: The aims of this study are 2-fold: to inventory the studies on FHIR semantic interoperability resources and terminologies and to identify and classify the approaches and contributions proposed in these studies. Methods: A systematic mapping review (SMR) was conducted using 10 electronic databases as sources of information for inventory and review studies published during 2012 to 2022 on the development and improvement of semantic interoperability using the FHIR standard. Results: A total of 70 FHIR studies were selected and analyzed to identify FHIR resource types and terminologies from a semantic perspective. The proposed semantic approaches were classified into 6 categories, namely mapping (31/126, 24.6\%), terminology services (18/126, 14.3\%), resource description framework or web ontology language--based proposals (24/126, 19\%), annotation proposals (18/126, 14.3\%), machine learning (ML) and natural language processing (NLP) proposals (20/126, 15.9\%), and ontology-based proposals (15/126, 11.9\%). From 2012 to 2022, there has been continued research in 6 categories of approaches as well as in new and emerging annotations and ML and NLP proposals. This SMR also classifies the contributions of the selected studies into 5 categories: framework or architecture proposals, model proposals, technique proposals, comparison services, and tool proposals. The most frequent type of contribution is the proposal of a framework or architecture to enable semantic interoperability. Conclusions: This SMR provides a classification of the different solutions proposed to address semantic interoperability using FHIR at different levels: collecting, extracting and annotating data, modeling electronic health record data from legacy systems, and applying transformation and mapping to FHIR models and terminologies. The use of ML and NLP for unstructured data is promising and has been applied to specific use case scenarios. In addition, terminology services are needed to accelerate their use and adoption; furthermore, techniques and tools to automate annotation and ontology comparison should help reduce human interaction.},
  langid = {english},
  file = {/Users/dkapitan/Zotero/storage/36M2PLBD/Amar et al. - 2024 - Electronic Health Record and Semantic Issues Using.pdf;/Users/dkapitan/Zotero/storage/H9WMEGQA/e45209.html}
}

@inproceedings{armbrust2021lakehouse,
  title = {Lakehouse: {{A New Generation}} of {{Open Platforms}} That {{Unify Data Warehousing}} and {{Advanced Analytics}}},
  booktitle = {11th {{Annual Conference}} on {{Innovative Data Systems Research}} ({{CIDR}} '21)},
  author = {Armbrust, Michael and Ghodsi, Ali and Xin, Reynold and Zaharia, Matei},
  year = {2021},
  pages = {8},
  abstract = {This paper argues that the data warehouse architecture as we know it today will wither in the coming years and be replaced by a new architectural pattern, the Lakehouse, which will (i) be based on open direct-access data formats, such as Apache Parquet, (ii) have firstclass support for machine learning and data science, and (iii) offer state-of-the-art performance. Lakehouses can help address several major challenges with data warehouses, including data staleness, reliability, total cost of ownership, data lock-in, and limited use-case support. We discuss how the industry is already moving toward Lakehouses and how this shift may affect work in data management. We also report results from a Lakehouse system using Parquet that is competitive with popular cloud data warehouses on TPC-DS.},
  langid = {english},
  file = {/Users/dkapitan/Zotero/storage/8XX2TSTM/Armbrust et al. - 2021 - Lakehouse A New Generation of Open Platforms that.pdf}
}

@article{ashworth2022free,
  title = {A {{Free}}, {{Open-Source}}, {{Offline Digital Health System}} for {{Refugee Care}}},
  author = {Ashworth, Henry and Ebrahim, Senan and Ebrahim, Hassaan and Bhaiwala, Zahra and Chilazi, Michael},
  year = {2022},
  month = feb,
  journal = {JMIR Medical Informatics},
  volume = {10},
  number = {2},
  pages = {e33848},
  issn = {2291-9694},
  doi = {10.2196/33848},
  urldate = {2024-04-18},
  abstract = {Background: Rise of conflict, extreme weather events, and pandemics have led to larger displaced populations worldwide. Displaced populations have unique acute and chronic health needs that must be met by low-resource health systems. Electronic health records (EHRs) have been shown to improve health outcomes in displaced populations, but need to be adapted to meet the constraints of these health systems. Objective: The aim of this viewpoint is to describe the development and deployment of an EHR designed to care for displaced populations in low-resource settings. Methods: Using a human-centered design approach, we conducted in-depth interviews and focus groups with patients, health care providers, and administrators in Lebanon and Jordan to identify the essential EHR features. These features, including modular workflows, multilingual interfaces, and offline-first capabilities, led to the development of the Hikma Health EHR, which has been deployed in Lebanon and Nicaragua. Results: We report the successes and challenges from 12 months of Hikma Health EHR deployment in a mobile clinic providing care to Syrian refugees in Bekaa Valley, Lebanon. Successes include the EHR's ability to (1) increase clinical efficacy by providing detailed patient records, (2) be adaptable to the threats of COVID-19, and (3) improve organizational planning. Lessons learned include technical fixes to methods of identifying patients through name or their medical record ID. Conclusions: As the number of displaced people continues to rise globally, it is imperative that solutions are created to help maximize the health care they receive. Free, open-sourced, and adaptable EHRs can enable organizations to better provide for displaced populations.},
  langid = {english},
  file = {/Users/dkapitan/Zotero/storage/VZXUL26D/Ashworth et al. - 2022 - A Free, Open-Source, Offline Digital Health System.pdf}
}

@article{ayaz2021fast,
  title = {The {{Fast Health Interoperability Resources}} ({{FHIR}}) {{Standard}}: {{Systematic Literature Review}} of {{Implementations}}, {{Applications}}, {{Challenges}} and {{Opportunities}}},
  shorttitle = {The {{Fast Health Interoperability Resources}} ({{FHIR}}) {{Standard}}},
  author = {Ayaz, Muhammad and Pasha, Muhammad F and Alzahrani, Mohammed Y and Budiarto, Rahmat and Stiawan, Deris},
  year = {2021},
  month = jul,
  journal = {JMIR Medical Informatics},
  volume = {9},
  number = {7},
  pages = {e21929},
  issn = {2291-9694},
  doi = {10.2196/21929},
  abstract = {Background Information technology has shifted paper-based documentation in the health care sector into a digital form, in which patient information is transferred electronically from one place to another. However, there remain challenges and issues to resolve in this domain owing to the lack of proper standards, the growth of new technologies (mobile devices, tablets, ubiquitous computing), and health care providers who are reluctant to share patient information. Therefore, a solid systematic literature review was performed to understand the use of this new technology in the health care sector. To the best of our knowledge, there is a lack of comprehensive systematic literature reviews that focus on Fast Health Interoperability Resources (FHIR)-based electronic health records (EHRs). In addition, FHIR is the latest standard, which is in an infancy stage of development. Therefore, this is a hot research topic with great potential for further research in this domain. Objective The main aim of this study was to explore and perform a systematic review of the literature related to FHIR, including the challenges, implementation, opportunities, and future FHIR applications. Methods In January 2020, we searched articles published from January 2012 to December 2019 via all major digital databases in the field of computer science and health care, including ACM, IEEE Explorer, Springer, Google Scholar, PubMed, and ScienceDirect. We identified 8181 scientific articles published in this field, 80 of which met our inclusion criteria for further consideration. Results The selected 80 scientific articles were reviewed systematically, and we identified open questions, challenges, implementation models, used resources, beneficiary applications, data migration approaches, and goals of FHIR. Conclusions The literature analysis performed in this systematic review highlights the important role of FHIR in the health care domain in the near future.},
  pmcid = {PMC8367140},
  pmid = {34328424},
  file = {/Users/dkapitan/Zotero/storage/GPZC3SWK/Ayaz et al. - 2021 - The Fast Health Interoperability Resources (FHIR) .pdf}
}

@article{ayaz2023transforming,
  title = {Transforming {{Healthcare Analytics}} with {{FHIR}}: {{A Framework}} for {{Standardizing}} and {{Analyzing Clinical Data}}},
  shorttitle = {Transforming {{Healthcare Analytics}} with {{FHIR}}},
  author = {Ayaz, Muhammad and Pasha, Muhammad Fermi and Alahmadi, Tahani Jaser and Abdullah, Nik Nailah Binti and Alkahtani, Hend Khalid},
  year = {2023},
  month = jan,
  journal = {Healthcare},
  volume = {11},
  number = {12},
  pages = {1729},
  publisher = {Multidisciplinary Digital Publishing Institute},
  issn = {2227-9032},
  doi = {10.3390/healthcare11121729},
  urldate = {2024-01-08},
  abstract = {In this study, we discussed our contribution to building a data analytic framework that supports clinical statistics and analysis by leveraging a scalable standards-based data model named Fast Healthcare Interoperability Resource (FHIR). We developed an intelligent algorithm that is used to facilitate the clinical data analytics process on FHIR-based data. We designed several workflows for patient clinical data used in two hospital information systems, namely patient registration and laboratory information systems. These workflows exploit various FHIR Application programming interface (APIs) to facilitate patient-centered and cohort-based interactive analyses. We developed an FHIR database implementation that utilizes FHIR APIs and a range of operations to facilitate descriptive data analytics (DDA) and patient cohort selection. A prototype user interface for DDA was developed with support for visualizing healthcare data analysis results in various forms. Healthcare professionals and researchers would use the developed framework to perform analytics on clinical data used in healthcare settings. Our experimental results demonstrate the proposed framework's ability to generate various analytics from clinical data represented in the FHIR resources.},
  copyright = {http://creativecommons.org/licenses/by/3.0/},
  langid = {english},
  keywords = {data analysis,data analytics,EHR,EMR,FHIR},
  file = {/Users/dkapitan/Zotero/storage/A9EQNSN2/Ayaz et al. - 2023 - Transforming Healthcare Analytics with FHIR A Fra.pdf}
}

@article{bagayoko2023effect,
  title = {Effect of High-Risk versus Low-Risk Pregnancy at the First Antenatal Care Visit on the Occurrence of Complication during Pregnancy and Labour or Delivery in {{Kenya}}: A Double-Robust Estimation},
  shorttitle = {Effect of High-Risk versus Low-Risk Pregnancy at the First Antenatal Care Visit on the Occurrence of Complication during Pregnancy and Labour or Delivery in {{Kenya}}},
  author = {Bagayoko, Moussa and Kadengye, Damazo T. and Odero, Henry Owoko and Izudi, Jonathan},
  year = {2023},
  month = oct,
  journal = {BMJ Open},
  volume = {13},
  number = {10},
  pages = {e072451},
  publisher = {British Medical Journal Publishing Group},
  issn = {2044-6055, 2044-6055},
  doi = {10.1136/bmjopen-2023-072451},
  urldate = {2024-02-27},
  abstract = {Objectives We evaluated the causal effects of high-risk versus low-risk pregnancy at the first antenatal care (ANC) visit on the occurrence of complications during pregnancy and labour or delivery among women in Kenya. Methods We designed a quasi-experimental study using observational data from a large mobile health wallet programme, with the exposure as pregnancy risk at the first ANC visit, measured on a binary scale (low vs high). Complications during pregnancy and at labour or delivery were the study outcomes on a binary scale (yes vs no). Causal effects of the exposure were examined using a double-robust estimation, reported as an OR with a 95\% CI. Results We studied 4419 women aged 10--49 years (mean, 25.6{\textpm}6.27 years), with the majority aged 20--29 years (53.4\%) and rural residents (87.4\%). Of 3271 women with low-risk pregnancy at the first ANC visit, 833 (25.5\%) had complications during pregnancy while 1074 (32.8\%) had complications at labour/delivery. Conversely, of 1148 women with high-risk pregnancy at the first ANC visit, 343 (29.9\%) had complication during pregnancy while 488 (42.5\%) had complications at labour delivery. Multivariable adjusted analysis showed that women with high-risk pregnancy at the time of first ANC attendance had a higher occurrence of pregnancy during pregnancy (adjusted OR (aOR) 1.22, 95\% CI 1.02 to 1.46) and labour or delivery (aOR 1.20, 95\% CI 1.03 to 1.41). In the double-robust estimation, a high-risk pregnancy at first ANC visit increased the occurrence of complications during pregnancy (OR 1.23, 95\% CI 1.04 to 1.46) and labour or delivery (OR 1.24, 95\% CI 1.07 to 1.45). Conclusion Women with a high-risk pregnancy at the first ANC visit have an increased occurrence of complications during pregnancy and labour or delivery. These women should be identified early for close and appropriate obstetric and intrapartum monitoring and care to ensure maternal and neonatal survival.},
  chapter = {Global health},
  copyright = {{\copyright} Author(s) (or their employer(s)) 2023. Re-use permitted under CC BY-NC. No commercial re-use. See rights and permissions. Published by BMJ.. http://creativecommons.org/licenses/by-nc/4.0/This is an open access article distributed in accordance with the Creative Commons Attribution Non Commercial (CC BY-NC 4.0) license, which permits others to distribute, remix, adapt, build upon this work non-commercially, and license their derivative works on different terms, provided the original work is properly cited, appropriate credit is given, any changes made indicated, and the use is non-commercial. See:~http://creativecommons.org/licenses/by-nc/4.0/.},
  langid = {english},
  pmid = {37899166},
  keywords = {Antenatal,Maternal medicine,NEONATOLOGY,Risk management},
  file = {/Users/dkapitan/Zotero/storage/IGJM9858/Bagayoko et al. - 2023 - Effect of high-risk versus low-risk pregnancy at t.pdf}
}

@article{baldwin2008architecture,
  title = {The {{Architecture}} of {{Platforms}}: {{A Unified View}}},
  shorttitle = {The {{Architecture}} of {{Platforms}}},
  author = {Baldwin, Carliss and Woodard, C. Jason},
  year = {2008},
  month = sep,
  journal = {Platforms, Markets and Innovation},
  doi = {10.2139/ssrn.1265155},
  abstract = {The central role of "platform" products and services in mediating the activities of disaggregated "clusters" or "ecosystems" of firms has been widely recognized. But platforms and the systems in which they are embedded are very diverse. In particular, platforms may exist within firms as product lines, across firms as multi-product systems, and in the form of multi-sided markets. In this paper we argue that there is a fundamental unity in the architecture of platforms. Platform architectures are modularizations of complex systems in which certain components (the platform itself) remain stable, while others (the complements) are encouraged to vary in crosssection or over time. Among the most stable elements in a platform architecture are the modular interfaces that mediate between the platform and its complements. These interfaces are even more stable than the interior core of the platform, thus control over the interfaces amounts to control over the platform and its evolution. We describe three ways of representing platform architectures: network graphs, design structure matrices and layer maps. We conclude by addressing a number of fundamental strategic questions suggested by a unified view of platforms.},
  file = {/Users/dkapitan/Zotero/storage/UDQ8ER38/Baldwin and Woodard - The Architecture of Platforms A Unified View.pdf;/Users/dkapitan/Zotero/storage/ZZCZTMZG/Baldwin and Woodard - 2008 - The Architecture of Platforms A Unified View.pdf}
}

@article{baran1964distributed,
  title = {On {{Distributed Communications Networks}}},
  author = {Baran, P.},
  year = {1964},
  month = mar,
  journal = {IEEE Transactions on Communications Systems},
  volume = {12},
  number = {1},
  pages = {1--9},
  issn = {1558-2647},
  doi = {10.1109/TCOM.1964.1088883},
  urldate = {2024-08-12},
  abstract = {This paper briefly reviews the distributed communication network concept in which each station is connected to all adjacent stations rather than to a few switching points, as in a centralized system. The payoff for a distributed configuration in terms of survivability in the cases of enemy attack directed against nodes, links or combinations of nodes and links is demonstrated. A comparison is made between diversity of assignment and perfect switching in distributed networks, and the feasibility of using low-cost unreliable communication links, even links so unreliable as to be unusable in present type networks, to form highly reliable networks is discussed. The requirements for a future all-digital data distributed network which provides common user service for a wide range of users having different requirements is considered. The use of a standard format message block permits building relatively simple switching mechanisms using an adaptive store-and-forward routing policy to handle all forms of digital data including digital voice. This network rapidly responds to changes in the network status. Recent history of measured network traffic is used to modify path selection. Simulation results are shown to indicate that highly efficient routing can be performed by local control without the necessity for any central, and therefore vulnerable, control point.},
  keywords = {Buildings,Centralized control,Communication networks,Communication switching,Communication system control,History,Information systems,Network synthesis,Routing,Telecommunication network reliability},
  file = {/Users/dkapitan/Zotero/storage/GXJYF89Z/Baran - 1964 - On Distributed Communications Networks.pdf}
}

@article{barcenafedxai,
  title = {Fed-{{XAI}}: {{Federated Learning}} of {{Explainable Artificial Intelligence Models}}},
  author = {B{\'a}rcena, Jos{\'e} Luis Corcuera and Daole, Mattia and Ducange, Pietro and Marcelloni, Francesco and Renda, Alessandro and Ruffini, Fabrizio and Schiavo, Alessio},
  abstract = {The current era is characterized by an increasing pervasiveness of applications and services based on data processing and often built on Artificial Intelligence (AI) and, in particular, Machine Learning (ML) algorithms. In fact, extracting insights from data is so common in daily life of individuals, companies, and public entities and so relevant for the market players, to become an important matter of interest for institutional organizations. The theme is so relevant that ad hoc regulations have been proposed. One important aspect is given by the capability of the applications to tackle the data privacy issue. Additionally, depending on the specific application field, paramount importance is given to the possibility for the humans to understand why a certain AI/ML-based application is providing that specific output. In this paper, we discuss the concept of Federated Learning of eXplainable AI (XAI) models, in short FED-XAI, purposely designed to address these two requirements simultaneously. AI/ML models are trained with the simultaneous goals of preserving the data privacy (Federated Learning (FL) side) and ensuring a certain level of explainability of the system (XAI side). We first introduce the motivations at the foundation of FL and XAI, along with their basic concepts; then, we discuss the current status of this field of study, providing a brief survey regarding approaches, models, and results. Finally, we highlight the main future challenges.},
  langid = {english},
  file = {/Users/dkapitan/Zotero/storage/6NGRFDBD/Bárcena et al. - Fed-XAI Federated Learning of Explainable Artific.pdf}
}

@article{bartlett2021insights,
  title = {Insights into the Design, Development and Implementation of a Novel Digital Health Tool for Skilled Birth Attendants to Support Quality Maternity Care in {{Kenya}}},
  author = {Bartlett, Linda and Avery, Lisa and Ponnappan, Priya and Chelangat, Judith and Cheruiyot, Jackline and Matthews, Rose and Rocheleau, Mary and Tikkanen, Mari and Allen, Mark and Amendola, Paul and Labrique, Alain},
  year = {2021},
  month = aug,
  journal = {Family Medicine and Community Health},
  volume = {9},
  number = {3},
  pages = {e000845},
  issn = {2305-6983},
  doi = {10.1136/fmch-2020-000845},
  urldate = {2024-09-06},
  pmcid = {PMC8336131},
  pmid = {34344764},
  file = {/Users/dkapitan/Zotero/storage/NU4E5NNI/Bartlett et al. - 2021 - Insights into the design, development and implemen.pdf}
}

@article{beck2019hourglass,
  title = {On the Hourglass Model},
  author = {Beck, Micah},
  year = {2019},
  month = jun,
  journal = {Communications of the ACM},
  volume = {62},
  number = {7},
  pages = {48--57},
  issn = {0001-0782, 1557-7317},
  doi = {10.1145/3274770},
  abstract = {Used in the design of the Internet and Unix, the layered services of the hourglass model have enabled viral adoption and deployment scalability.},
  langid = {english},
  file = {/Users/dkapitan/Zotero/storage/NKGQZL5V/Beck - 2019 - On the hourglass model.pdf}
}

@article{belov2021analysis,
  title = {Analysis of {{Big Data Storage Tools}} for {{Data Lakes}} Based on {{Apache Hadoop Platform}}},
  author = {Belov, Vladimir and Nikulchev, Evgeny},
  year = {2021},
  journal = {International Journal of Advanced Computer Science and Applications},
  volume = {12},
  number = {8},
  issn = {21565570, 2158107X},
  doi = {10.14569/IJACSA.2021.0120864},
  urldate = {2024-04-18},
  abstract = {When developing large data processing systems, the question of data storage arises. One of the modern tools for solving this problem is the so-called data lakes. Many implementations of data lakes use Apache Hadoop as a basic platform. Hadoop does not have a default data storage format, which leads to the task of choosing a data format when designing a data processing system. To solve this problem, it is necessary to proceed from the results of the assessment according to several criteria. In turn, experimental evaluation does not always give a complete understanding of the possibilities for working with a particular data storage format. In this case, it is necessary to study the features of the format, its internal structure, recommendations for use, etc. The article describes the features of both widely used data storage formats and the currently gaining popularity.},
  langid = {english},
  file = {/Users/dkapitan/Zotero/storage/VYIRJ6C8/Belov and Nikulchev - 2021 - Analysis of Big Data Storage Tools for Data Lakes .pdf}
}

@article{benda2024designing,
  title = {Designing {{Electronic Data Capture Systems}} for {{Sustainability}} in {{Low-Resource Settings}}: {{Viewpoint With Lessons Learned From Ethiopia}} and {{Myanmar}}},
  shorttitle = {Designing {{Electronic Data Capture Systems}} for {{Sustainability}} in {{Low-Resource Settings}}},
  author = {Benda, Natalie and Dougherty, Kylie and Gobezayehu, Abebe Gebremariam and Cranmer, John N. and Zawtha, Sakie and Andreadis, Katerina and Biza, Heran and Creber, Ruth Masterson},
  year = {2024},
  month = feb,
  journal = {JMIR Public Health and Surveillance},
  volume = {10},
  number = {1},
  pages = {e47703},
  publisher = {JMIR Publications Inc., Toronto, Canada},
  doi = {10.2196/47703},
  urldate = {2024-05-27},
  abstract = {Electronic data capture (EDC) is a crucial component in the design, evaluation, and sustainment of population health interventions. Low-resource settings, however, present unique challenges for developing a robust EDC system due to limited financial capital, differences in technological infrastructure, and insufficient involvement of those who understand the local context. Current literature focuses on the evaluation of health interventions using EDC but does not provide an in-depth description of the systems used or how they are developed. In this viewpoint, we present case descriptions from 2 low- and middle-income countries: Ethiopia and Myanmar. We address a gap in evidence by describing each EDC system in detail and discussing the pros and cons of different approaches. We then present common lessons learned from the 2 case descriptions as recommendations for considerations in developing and implementing EDC in low-resource settings, using a sociotechnical framework for studying health information technology in complex adaptive health care systems. Our recommendations highlight the importance of selecting hardware compatible with local infrastructure, using flexible software systems that facilitate communication across different languages and levels of literacy, and conducting iterative, participatory design with individuals with deep knowledge of local clinical and cultural norms.},
  copyright = {Unless stated otherwise, all articles are open-access distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/2.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work ("first published in the Journal of Medical Internet Research...") is properly cited with original URL and bibliographic citation information. The complete bibliographic information, a link to the original publication on http://www.jmir.org/, as well as this copyright and license information must be included.},
  langid = {english},
  file = {/Users/dkapitan/Zotero/storage/BYVZ2Q3U/Benda et al. - 2024 - Designing Electronic Data Capture Systems for Sust.pdf}
}

@book{benkler2006wealth,
  title = {The Wealth of Networks: How Social Production Transforms Markets and Freedom},
  shorttitle = {The Wealth of Networks},
  author = {Benkler, Yochai},
  year = {2006},
  publisher = {Yale University Press},
  address = {New Haven London},
  abstract = {Introduction: a moment of opportunity and challenge -- The networked information economy -- Some basic economics of information production and innovation -- Peer production and sharing -- The economics of social production -- The political economy of property and commons -- Individual freedom: autonomy, information, and law -- Political freedom part 1: the trouble with mass media -- Political freedom part 2: emergence of the networked public sphere -- Cultural freedom: a culture both plastic and critical -- Justice and development -- Social ties: networking together -- Policies of freedom at a moment of transformation -- The battle over the institutional ecology of the digital environment -- Conclusion: the stakes of information law and policy},
  isbn = {978-0-300-11056-2 978-0-300-12577-1},
  langid = {english},
  file = {/Users/dkapitan/Zotero/storage/82CL6MM6/Benkler - 2006 - The wealth of networks how social production tran.pdf}
}

@article{benklerconsumers,
  title = {From {{Consumers}} to {{Users}}: {{Shifting}} the {{Deeper Structures}} of {{Regulation Toward Sustainable Commons}} and {{User Access}}},
  author = {Benkler, Yochai},
  volume = {52},
  langid = {english},
  file = {/Users/dkapitan/Zotero/storage/GXCBVD54/Benkler - From Consumers to Users Shifting the Deeper Struc.pdf}
}

@article{bergman2022business,
  title = {Business Model Archetypes for Data Marketplaces in the Automotive Industry},
  author = {Bergman, R{\^o}my and Abbas, Antragama Ewa and Jung, Sven and Werker, Claudia and {de Reuver}, Mark},
  year = {2022},
  month = jun,
  journal = {Electronic Markets},
  volume = {32},
  number = {2},
  pages = {747--765},
  issn = {1422-8890},
  doi = {10.1007/s12525-022-00547-x},
  urldate = {2024-05-27},
  abstract = {Policymakers and analysts are heavily promoting data marketplaces to foster data trading between companies. Existing business model literature covers individually owned, multilateral data marketplaces. However, these particular types of data marketplaces hardly reach commercial exploitation. This paper develops business model archetypes for the full array of data marketplace types, ranging from private to independent ownership and from a hierarchical to a market orientation. Through exploratory interviews and case analyses, we create a business model taxonomy. Patterns in our taxonomy reveal four business model archetypes. We find that privately-owned data marketplaces with hierarchical orientation apply the aggregating data marketplace archetype. Consortium-owned data marketplaces apply the archetypes of aggregating data marketplace with additional brokering service and consulting data marketplace. Independently owned data marketplaces with market orientation apply the facilitating data marketplace archetype. Our results provide a basis for configurational theory that explains the performance of data marketplace business models. Our results also provide a basis for specifying boundary conditions for theory on data marketplace business models, as, for instance, the importance of network effects differs strongly between the archetypes.},
  langid = {english},
  keywords = {L10,L22,L86,L89,Z00},
  file = {/Users/dkapitan/Zotero/storage/ID3JBSXD/Bergman et al. - 2022 - Business model archetypes for data marketplaces in.pdf}
}

@article{beyan2020distributed,
  title = {Distributed {{Analytics}} on {{Sensitive Medical Data}}: {{The Personal Health Train}}},
  shorttitle = {Distributed {{Analytics}} on {{Sensitive Medical Data}}},
  author = {Beyan, Oya and Choudhury, Ananya and {van Soest}, Johan and Kohlbacher, Oliver and Zimmermann, Lukas and Stenzhorn, Holger and Karim, Md. Rezaul and Dumontier, Michel and Decker, Stefan and {da Silva Santos}, Luiz Olavo Bonino and Dekker, Andre},
  year = {2020},
  month = jan,
  journal = {Data Intelligence},
  volume = {2},
  number = {1-2},
  pages = {96--107},
  issn = {2641-435X},
  doi = {10.1162/dint_a_00032},
  urldate = {2023-02-16},
  abstract = {In recent years, as newer technologies have evolved around the healthcare ecosystem, more and more data have been generated. Advanced analytics could power the data collected from numerous sources, both from healthcare institutions, or generated by individuals themselves via apps and devices, and lead to innovations in treatment and diagnosis of diseases; improve the care given to the patient; and empower citizens to participate in the decision-making process regarding their own health and well-being. However, the sensitive nature of the health data prohibits healthcare organizations from sharing the data. The Personal Health Train (PHT) is a novel approach, aiming to establish a distributed data analytics infrastructure enabling the (re)use of distributed healthcare data, while data owners stay in control of their own data. The main principle of the PHT is that data remain in their original location, and analytical tasks visit data sources and execute the tasks. The PHT provides a distributed, flexible approach to use data in a network of participants, incorporating the FAIR principles. It facilitates the responsible use of sensitive and/or personal data by adopting international principles and regulations. This paper presents the concepts and main components of the PHT and demonstrates how it complies with FAIR principles.},
  file = {/Users/dkapitan/Zotero/storage/SGX995AZ/Beyan et al. - 2020 - Distributed Analytics on Sensitive Medical Data T.pdf}
}

@article{bharatleveraging,
  title = {Leveraging {{ABDM Building Blocks}}:},
  author = {Bharat, Ayushman},
  langid = {english},
  file = {/Users/dkapitan/Zotero/storage/ISTVTZA3/Bharat - Leveraging ABDM Building Blocks.pdf}
}

@article{bishop2007reflexive,
  title = {A {{Reflexive Account}} of {{Reusing Qualitative Data}}: {{Beyond}}                     {{Primary}}/{{Secondary Dualism}}},
  shorttitle = {A {{Reflexive Account}} of {{Reusing Qualitative Data}}},
  author = {Bishop, Libby},
  year = {2007},
  month = may,
  journal = {Sociological Research Online},
  volume = {12},
  number = {3},
  pages = {43--56},
  publisher = {SAGE Publications Ltd},
  issn = {1360-7804},
  doi = {10.5153/sro.1553},
  urldate = {2024-08-26},
  abstract = {Though secondary analysis of qualitative data is becoming more prevalent, relatively few methodological studies exist that provide reflection on the actual, not idealised, process. This paper offers a reflexive account of secondary analysis focused on the topic of convenience food and choice. Several phases of the research process are examined: understanding context, defining a subject area, finding data and sampling, later sampling and topic refinement, and relating to transcripts. For each phase, I explore if reusing data is different from using it in the first instance, and if so, how those differences manifest themselves. The paper closes with reflections on the differences, similarities, and relationships between primary and secondary analysis of qualitative data. Although differences exist regarding the researcher-respondent relationship, primary and secondary analyses are more alike than not. The suitability of each approach can only be assessed in light of a particular research question.},
  langid = {english},
  file = {/Users/dkapitan/Zotero/storage/3N2V35N9/Bishop - 2007 - A Reflexive Account of Reusing Qualitative Data B.pdf}
}

@article{bisquerthealthmesh,
  title = {{{HealthMesh}}: {{An Architectural Framework}} for {{Federated Healthcare Data Management}}},
  author = {Bisquert, Aniol and Hmimou, Achraf and Berral, Josep Ll and {Gutierrez-Torre}, Alberto and Romero, Oscar},
  abstract = {Recently, significant milestones have been achieved in the field of healthcare data analysis. However, alongside these accomplishments, substantial data-related challenges have emerged in the domain of big data management. Modern healthcare projects are no more dealing with a single data repository but many heterogeneous ones and must overcome data variety, privacy and governance issues. Yet, current solutions face a privacy-decentralization trade-off. To address this dual challenge, we introduce HealthMesh, a novel layered architectural framework based on the Data Mesh principles, providing a domaindecentralised paradigm. In addition, the framework incorporates a Semantic Data Model which establishes robust governance, enables interoperability and guarantees policy compliance for all the data assets. To demonstrate the capabilities of the proposed approach, we provide an illustrative example inspired by the use case of the INCISIVE project for breast cancer analytics. Overall, this work makes a significant contribution on collecting key challenges, identifying actors and providing a set of components and guidelines for establishing a holistic framework for the complex field of healthcare data management.},
  langid = {english},
  file = {/Users/dkapitan/Zotero/storage/SR28BEVA/bidquert2024healthmesh.pdf}
}

@article{bonina2021digital,
  title = {Digital Platforms for Development: {{Foundations}} and Research Agenda},
  shorttitle = {Digital Platforms for Development},
  author = {Bonina, Carla and Koskinen, Kari and Eaton, Ben and Gawer, Annabelle},
  year = {2021},
  journal = {Information Systems Journal},
  volume = {31},
  number = {6},
  pages = {869--902},
  issn = {1365-2575},
  doi = {10.1111/isj.12326},
  urldate = {2024-08-13},
  abstract = {Digital platforms hold a central position in today's world economy and are said to offer a great potential for the economies and societies in the global South. Yet, to date, the scholarly literature on digital platforms has largely concentrated on business while their developmental implications remain understudied. In part, this is because digital platforms are a challenging research object due to their lack of conceptual definition, their spread across different regions and industries, and their intertwined nature with institutions, actors and digital technologies. The purpose of this article is to contribute to the ongoing debate in information systems and ICT4D research to understand what digital platforms mean for development. To do so, we first define what digital platforms are and differentiate between transaction and innovation platforms, and explain their key characteristics in terms of purpose, research foundations, material properties and business models. We add the socio-technical context digital platforms operate and the linkages to developmental outcomes. We then conduct an extensive review to explore what current areas, developmental goals, tensions and issues emerge in the literature on platforms and development and identify relevant gaps in our knowledge. We later elaborate on six research questions to advance the studies on digital platforms for development: on indigenous innovation, digital platforms and institutions, on exacerbation of inequalities, on alternative forms of value, on the dark side of platforms and on the applicability of the platform typology for development.},
  copyright = {{\copyright} 2021 The Authors. Information Systems Journal published by John Wiley \& Sons Ltd.},
  langid = {english},
  file = {/Users/dkapitan/Zotero/storage/2WXJFWD7/Bonina et al. - 2021 - Digital platforms for development Foundations and.pdf;/Users/dkapitan/Zotero/storage/6W36Y4VW/isj.html}
}

@article{braa2004networks,
  title = {Networks of Action: Sustainable Health Information Systems across Developing Countries},
  shorttitle = {Networks of Action},
  author = {Braa, J{\o}rn and Monteiro, Eric and Sahay, Sundeep},
  year = {2004},
  journal = {MIS quarterly},
  eprint = {25148643},
  eprinttype = {jstor},
  pages = {337--362},
  publisher = {JSTOR},
  urldate = {2024-05-15},
  file = {/Users/dkapitan/Zotero/storage/VTQS7RUK/Braa et al. - 2004 - Networks of action sustainable health information.pdf}
}

@article{braa2007developing,
  title = {Developing {{Health Information Systems}} in {{Developing Countries}}: {{The Flexible Standards Strategy}}},
  shorttitle = {Developing {{Health Information Systems}} in {{Developing Countries}}},
  author = {{Braa} and {Hanseth} and {Heywood} and {Mohammed} and {Shaw}},
  year = {2007},
  journal = {MIS Quarterly},
  volume = {31},
  number = {2},
  eprint = {10.2307/25148796},
  eprinttype = {jstor},
  pages = {381},
  issn = {02767783},
  doi = {10.2307/25148796},
  urldate = {2024-05-15},
  langid = {english},
  file = {/Users/dkapitan/Zotero/storage/LE7IZVAD/Braa et al. - 2007 - Developing Health Information Systems in Developin.pdf}
}

@misc{braa2023design,
  title = {Design {{Theory}} for {{Societal Digital Transformation}}: {{The Case}} of {{Digital Global Health}}},
  shorttitle = {Design {{Theory}} for {{Societal Digital Transformation}}},
  author = {Braa, Jorn and Sahay, Sundeep and Monteiro, Eric},
  year = {2023},
  month = nov,
  eprint = {2311.09173},
  primaryclass = {cs},
  doi = {0.17705/1jais.00816},
  urldate = {2024-05-15},
  abstract = {With societal challenges, including but not limited to human development, equity, social justice, and climate change, societal-level digital transformation (SDT) is of imminent relevance and theoretical interest. While building on local-level efforts, societal-level transformation is a nonlinear extension of the local level. Unfortunately, academic discourse on digital transformation has largely left SDT unaccounted for. Drawing on more than 25 years of intensive, interventionist research engagement with the digital transformation of public healthcare information management and delivery in more than 80 countries in the Global South, we contribute to theorizing SDT in the form of a design theory consisting of six interconnected design principles. These design principles articulate the interplay and tensions of accommodating over time increased diversity and flexibility in digital solutions, while simultaneously connecting local, national, and regional/ global efforts.},
  archiveprefix = {arXiv},
  keywords = {Computer Science - Computers and Society},
  file = {/Users/dkapitan/Zotero/storage/LGRDK4DS/Braa et al. - 2023 - Design Theory for Societal Digital Transformation.pdf;/Users/dkapitan/Zotero/storage/ILIIV23G/2311.html}
}

@article{broyles2016shared,
  title = {Shared {{Longitudinal Health Records}} for {{Clinical}} and {{Population Health}}},
  author = {Broyles, David and Crichton, Ryan and Jolliffe, Bob and S{\ae}b{\o}, Johan Ivar and Dixon, Brian E.},
  year = {2016},
  journal = {Health Information Exchange},
  pages = {149--162},
  doi = {10.1016/B978-0-12-803135-3.00010-4},
  urldate = {2024-08-27},
  abstract = {The ability of a health information exchange to consolidate information, collected in multiple, disparate information systems, into a single, person-centric health record can provide a comprehensive and longitudinal representation of an individual's medical history. Shared, longitudinal health records can be leveraged to enhance the delivery of individual clinical care and provide opportunities to improve health outcomes at the population level. This chapter will describe the clinical benefits imparted by the shared health record (SHR) component of the OpenHIE infrastructure. It will also characterize the potential population health benefits of the aggregate level data contained and distributed by the Health Management Information System component of OpenHIE. The chapter will further discuss the implementation of these systems., By the end of the chapter, the reader should be able to:\ding{108}Identify and describe the differences among an electronic medical record, electronic health record, and a shared heath record.\ding{108}Explain the role of a shared health record in a health information exchange.\ding{108}List and describe the components of a shared health record.\ding{108}Discuss the role and benefits of a health management information system within a health information exchange.\ding{108}Define a population health indicator.\ding{108}Identify and describe application domains for a health management information system.\ding{108}Define a database management system.\ding{108}Compare the implications of implementing a shared health record using an electronic health record system versus a database management system.\ding{108}Discuss emerging trends likely to shape the evolution of shared health records and health management information systems.},
  pmcid = {PMC7150120},
  pmid = {null},
  file = {/Users/dkapitan/Zotero/storage/WET52AIR/Broyles et al. - 2016 - Shared Longitudinal Health Records for Clinical an.pdf}
}

@article{cascini2024health,
  title = {Health Data Sharing Attitudes towards Primary and Secondary Use of Data: A Systematic Review},
  shorttitle = {Health Data Sharing Attitudes towards Primary and Secondary Use of Data},
  author = {Cascini, Fidelia and Pantovic, Ana and {Al-Ajlouni}, Yazan A. and Puleo, Valeria and De Maio, Lucia and Ricciardi, Walter},
  year = {2024},
  month = may,
  journal = {eClinicalMedicine},
  volume = {71},
  pages = {102551},
  issn = {2589-5370},
  doi = {10.1016/j.eclinm.2024.102551},
  urldate = {2024-03-21},
  abstract = {Background To receive the best care, people share their health data (HD) with their health practitioners (known as sharing HD for primary purposes). However, during the past two decades, sharing for other (i.e., secondary) purposes has become of great importance in numerous fields, including public health, personalized medicine, research, and development. We aimed to conduct the first comprehensive overview of all studies that investigated people's HD sharing attitudes---along with associated barriers/motivators and significant influencing factors---for all data types and across both primary and secondary uses. Methods We searched PubMed, MEDLINE, PsycINFO, Web of Science, EMBASE, and CINAHL for relevant studies published in English between database inception and February 28, 2023, using a predefined set of keywords. Studies were included, regardless of their design, if they reported outcomes related to attitudes towards sharing HD. We extracted key data from the included studies, including the type of HD involved and findings related to: HD sharing attitudes (either in general or depending on type of data/user); barriers/motivators/benefits/concerns of the study participants; and sociodemographic and other variables that could impact HD sharing behaviour. The qualitative synthesis was conducted by dividing the studies according to the data type (resulting in five subgroups) as well as the purpose the data sharing was focused on (primary, secondary or both). The Newcastle--Ottawa Scale (NOS) was used to assess the quality of non-randomised studies. This work was registered with PROSPERO, CRD42023413822. Findings Of 2109 studies identified through our search, 116 were included in the qualitative synthesis, yielding a total of 228,501 participants and various types of HD represented: person-generated HD (n~=~17 studies and 10,771 participants), personal HD in general (n~=~69 studies and 117,054 participants), Biobank data (n~=~7 studies and 27,073 participants), genomic data (n~=~13 studies and 54,716 participants), and miscellaneous data (n~=~10 studies and 18,887 participants). The majority of studies had a moderate level of quality (83 [71.6\%] of 116 studies), but varying levels of quality were observed across the included studies. Overall, studies suggest that sharing intentions for primary purposes were observed to be high regardless of data type, and it was higher than sharing intentions for secondary purposes. Sharing for secondary purposes yielded variable findings, where both the highest and the lowest intention rates were observed in the case of studies that explored sharing biobank data (98\% and 10\%, respectively). Several influencing factors on sharing intentions were identified, such as the type of data recipient, data, consent. Further, concerns related to data sharing that were found to be mutual for all data types included privacy, security, and data access/control, while the perceived benefits included those related to improvements in healthcare. Findings regarding attitudes towards sharing varied significantly across sociodemographic factors and depended on data type and type of use. In most cases, these findings were derived from single studies and therefore warrant confirmations from additional studies. Interpretation Sharing health data is a complex issue that is influenced by various factors (the type of health data, the intended use, the data recipient, among others) and these insights could be used to overcome barriers, address people's concerns, and focus on spreading awareness about the data sharing process and benefits. Funding None.},
  keywords = {Biobank,Data sharing,Genomic data,Person-generated data,Personal health data,Secondary use},
  file = {/Users/dkapitan/Zotero/storage/VILMTDEP/cascini2024health.pdf;/Users/dkapitan/Zotero/storage/2CFANZZK/S2589537024001305.html}
}

@book{cavanillas2016new,
  title = {New {{Horizons}} for a {{Data-Driven Economy}}},
  editor = {Cavanillas, Jos{\'e} Mar{\'i}a and Curry, Edward and Wahlster, Wolfgang},
  year = {2016},
  publisher = {Springer International Publishing},
  address = {Cham},
  doi = {10.1007/978-3-319-21569-3},
  urldate = {2024-05-27},
  copyright = {http://creativecommons.org/licenses/by-nc/4.0},
  isbn = {978-3-319-21568-6 978-3-319-21569-3},
  langid = {english},
  file = {/Users/dkapitan/Zotero/storage/S8ICHIX3/Cavanillas et al. - 2016 - New Horizons for a Data-Driven Economy.pdf}
}

@misc{chapter,
  title = {{{CHAPTER}} 6: {{LINK THE DIGITAL HEALTH IMPLEMENTATION TO THE ENTERPRISE ARCHITECTURE}} from {{Digital}} Implementation Investment Guide ({{DIIG}}):: Integrating Digital Interventions into Health Programmes on {{JSTOR}}},
  urldate = {2024-03-12},
  howpublished = {https://www-jstor-org.dianus.libr.tue.nl/stable/resrep33205.12},
  file = {/Users/dkapitan/Zotero/storage/4Q39MGIH/resrep33205.html}
}

@misc{choi2020building,
  title = {Building {{Methods}} of {{Intelligent Data Catalog Based}} on {{Graph Database}} for {{Data Sharing Platform}}},
  author = {Choi, Mi-Young and Moon, Chang-Joo and Jung, Sung-Jae},
  year = {2020},
  number = {10},
  eprint = {10},
  publisher = {ICIC International 学会},
  doi = {10.24507/icicelb.11.10.953},
  urldate = {2024-04-08},
  abstract = {Recently, the private and public sectors are constantly registering various types of data on a data sharing platform or an open data platform and creating value through linkage and expansion of data. Data catalogs are tools that can help you quickly find and understand the data accumulated on these data-sharing platforms. In this paper, we propose a method to build a data catalog based on a graph database. In the graph database, the joins are significantly reduced compared to the relational type due to the structural characteristics, while the query processing performance is improved. We show the process of transferring the proposed data catalog from the relational data model to the graph data model. We show that the same information retrieval is performed with a simpler query and higher performance in the graph database.},
  archiveprefix = {ICIC International 学会},
  langid = {english},
  file = {/Users/dkapitan/Zotero/storage/DBN65XNN/Choi et al. - 2020 - Building Methods of Intelligent Data Catalog Based.pdf}
}

@inproceedings{choudhury2020personal,
  title = {Personal {{Health Train}} on {{FHIR}}: {{A Privacy Preserving Federated Approach}} for {{Analyzing FAIR Data}} in {{Healthcare}}},
  shorttitle = {Personal {{Health Train}} on {{FHIR}}},
  booktitle = {Machine {{Learning}}, {{Image Processing}}, {{Network Security}} and {{Data Sciences}}},
  author = {Choudhury, Ananya and {van Soest}, Johan and Nayak, Stuti and Dekker, Andre},
  editor = {Bhattacharjee, Arup and Borgohain, Samir Kr. and Soni, Badal and Verma, Gyanendra and Gao, Xiao-Zhi},
  year = {2020},
  series = {Communications in {{Computer}} and {{Information Science}}},
  pages = {85--95},
  publisher = {Springer},
  address = {Singapore},
  doi = {10.1007/978-981-15-6315-7_7},
  abstract = {Big data and machine learning applications focus on retrieving data on a central location for analysis. However, healthcare data can be sensitive in nature and as such difficult to share and make use for secondary purposes. Healthcare vendors are restricted to share data without proper consent from the patient. There is a rising awareness among individual patients as well regarding sharing their personal information due to ethical, legal and societal problems. The current data-sharing platforms in healthcare do not sufficiently handle these issues. The rationale of the Personal Health Train (PHT) approach shifts the focus from sharing data to sharing processing/analysis applications and their respective results. A prerequisite of the PHT-infrastructure is that the data is FAIR (findable, accessible, interoperable, reusable). The aim of the paper is to describe a methodology of finding the number of patients diagnosed with hypertension and calculate cohort statistics in a privacy-preserving federated manner. The whole process completes without individual patient data leaving the source. For this, we rely on the Fast Healthcare Interoperability Resources (FHIR) standard.},
  isbn = {9789811563157},
  langid = {english},
  keywords = {FAIR,FHIR,Personal health train},
  file = {/Users/dkapitan/Zotero/storage/MX4FY5MX/Choudhury et al. - 2020 - Personal Health Train on FHIR A Privacy Preservin.pdf}
}

@article{chukwu2022electricity,
  title = {Electricity, {{Computing Hardware}}, and {{Internet Infrastructures}} in {{Health Facilities}} in {{Sierra Leone}}: {{Field Mapping Study}}},
  shorttitle = {Electricity, {{Computing Hardware}}, and {{Internet Infrastructures}} in {{Health Facilities}} in {{Sierra Leone}}},
  author = {Chukwu, Emeka and Garg, Lalit and Foday, Edward and Konomanyi, Abdul and Wright, Royston and Smart, Francis},
  year = {2022},
  month = feb,
  journal = {JMIR Medical Informatics},
  volume = {10},
  number = {2},
  pages = {e30040},
  publisher = {JMIR Publications Inc., Toronto, Canada},
  doi = {10.2196/30040},
  urldate = {2024-03-08},
  abstract = {Background: Years of health information system investment in many countries have facilitated service delivery, surveillance, reporting, and monitoring. Electricity, computing hardware, and internet networks are vital for health facility--based information systems. Availability of these infrastructures at health facilities is crucial for achieving national digital health visions. Objective: The aim of this study was to gain insight into the state of computing hardware, electricity, and connectivity infrastructure at health facilities in Sierra Leone using a representative sample. Methods: Stratified sampling of 72 (out of 1284) health facilities distributed in all districts of Sierra Leone was performed, factoring in the rural-urban divide, digital health activity, health facility type, and health facility ownership. Enumerators visited each health facility over a 2-week period. Results: Among the 72 surveyed health facilities, 59 (82\%) do not have institutionally provided internet. Among the 15 Maternal and Child Health Posts, as a type of primary health care unit (PHU), 9 (60\%) use solar energy as their only electricity source and the other 6 (40\%) have no electricity source. Similarly, among the 13 hospitals, 5 (38\%) use a generator as a primary electricity source. All hospitals have at least one functional computer, although only 7 of the 13 hospitals have four or more functional computers. Similarly, only 2 of the 59 (3\%) PHUs have one computer each, and 37 (63\%) of the PHUs have one tablet device each. We consider this health care computing infrastructure mapping to be representative with a 95\% confidence level within an 11\% margin of error. Two-thirds of the PHUs have only alternate solar electricity, only 10 of the 72 surveyed health facilities have functional official internet, and most use suboptimal computing hardware. Overall, 43\% of the surveyed health facilities believe that inadequate electricity is the biggest threat to digitization. Similarly, 16 (22\%) of the 72 respondents stated that device theft is a primary hindrance to digitization. Conclusions: Electricity provision for off-electricity-grid health facilities using alternative and renewable energy sources is emerging. The current trend where GSM (Global System for Mobile Communication) service providers provide the internet to all health facilities may change to other promising alternatives. This study provides evidence of the critical infrastructure gaps in health facilities in Sierra Leone.},
  copyright = {This is an open-access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work, first published JMIR Medical Informatics, is properly cited. The complete bibliographic information, a link to the original publication on https://medinform.jmir.org/, as well as this copyright and license information must be included.},
  langid = {english},
  file = {/Users/dkapitan/Zotero/storage/JF2H5GJE/Chukwu et al. - 2022 - Electricity, Computing Hardware, and Internet Infr.pdf;/Users/dkapitan/Zotero/storage/CBPPS9SW/e30040.html}
}

@misc{cohort,
  title = {Cohort {{Profile}}: {{The Avon Longitudinal Study}} of {{Parents}} and {{Children}}: {{ALSPAC}} Mothers Cohort - {{PMC}}},
  urldate = {2024-04-16},
  howpublished = {https://www-ncbi-nlm-nih-gov.dianus.libr.tue.nl/pmc/articles/PMC3600619/},
  file = {/Users/dkapitan/Zotero/storage/QYKRCY5C/PMC3600619.html}
}

@misc{comparison,
  title = {Comparison of {{Open-Source Electronic Health Record Systems Based}} on {{Functional}} and {{User Performance Criteria}} - {{PMC}}},
  urldate = {2024-06-04},
  howpublished = {https://www-ncbi-nlm-nih-gov.dianus.libr.tue.nl/pmc/articles/PMC6517630/},
  file = {/Users/dkapitan/Zotero/storage/X6KCNUE9/PMC6517630.html}
}

@misc{contexture2023national,
  title = {National {{Networks}} and {{HIEs}}: {{The Various Crossroads}} of {{Data Exchange}}},
  shorttitle = {National {{Networks}} and {{HIEs}}},
  author = {Contexture},
  year = {2023},
  month = jan,
  journal = {Contexture},
  urldate = {2024-08-20},
  abstract = {Background~ Contexture, as a health information exchange (HIE), serves a critical role in the overall ecosystem of data exchange and electronic health record (EHR) connectivity. HIEs were born as},
  langid = {american},
  file = {/Users/dkapitan/Zotero/storage/3DC4T5DU/national-networks-and-health-information-exchanges-the-various-crossroads-of-data-exchange.html}
}

@article{cordes2024competing,
  title = {Competing Interests: Digital Health and Indigenous Data Sovereignty},
  shorttitle = {Competing Interests},
  author = {Cordes, Ashley and Bak, Marieke and Lyndon, Mataroria and Hudson, Maui and Fiske, Amelia and Celi, Leo Anthony and McLennan, Stuart},
  year = {2024},
  month = jul,
  journal = {npj Digital Medicine},
  volume = {7},
  number = {1},
  pages = {1--5},
  publisher = {Nature Publishing Group},
  issn = {2398-6352},
  doi = {10.1038/s41746-024-01171-z},
  urldate = {2024-08-16},
  abstract = {Digital health is increasingly promoting open health data. Although this open approach promises a number of benefits, it also leads to tensions with Indigenous data sovereignty movements led by Indigenous peoples around the world who are asserting control over the use of health data as a part of self-determination. Digital health has a role in improving access to services and delivering improved health outcomes for Indigenous communities. However, we argue that in order to be effective and ethical, it is essential that the field engages more with Indigenous peoples{\textasciiacute} rights and interests. We discuss challenges and possible improvements for data acquisition, management, analysis, and integration as they pertain to the health of Indigenous communities around the world.},
  copyright = {2024 The Author(s)},
  langid = {english},
  keywords = {Health policy,Medical research},
  file = {/Users/dkapitan/Zotero/storage/29GEZYK4/Cordes et al. - 2024 - Competing interests digital health and indigenous.pdf}
}

@article{cremonesi2023need,
  title = {The Need for Multimodal Health Data Modeling: {{A}} Practical Approach for a Federated-Learning Healthcare Platform},
  shorttitle = {The Need for Multimodal Health Data Modeling},
  author = {Cremonesi, Francesco and Planat, Vincent and Kalokyri, Varvara and Kondylakis, Haridimos and Sanavia, Tiziana and Miguel Mateos Resinas, Victor and Singh, Babita and Uribe, Silvia},
  year = {2023},
  month = may,
  journal = {Journal of Biomedical Informatics},
  volume = {141},
  pages = {104338},
  issn = {1532-0464},
  doi = {10.1016/j.jbi.2023.104338},
  urldate = {2024-01-16},
  abstract = {Federated learning initiatives in healthcare are being developed to collaboratively train predictive models without the need to centralize sensitive personal data. GenoMed4All is one such project, with the goal of connecting European clinical and --omics data repositories on rare diseases through a federated learning platform. Currently, the consortium faces the challenge of a lack of well-established international datasets and interoperability standards for federated learning applications on rare diseases. This paper presents our practical approach to select and implement a Common Data Model (CDM) suitable for the federated training of predictive models applied to the medical domain, during the initial design phase of our federated learning platform. We describe our selection process, composed of identifying the consortium's needs, reviewing our functional and technical architecture specifications, and extracting a list of business requirements. We review the state of the art and evaluate three widely-used approaches (FHIR, OMOP and Phenopackets) based on a checklist of requirements and specifications. We discuss the pros and cons of each approach considering the use cases specific to our consortium as well as the generic issues of implementing a European federated learning healthcare platform. A list of lessons learned from the experience in our consortium is discussed, from the importance of establishing the proper communication channels for all stakeholders to technical aspects related to --omics data. For federated learning projects focused on secondary use of health data for predictive modeling, encompassing multiple data modalities, a phase of data model convergence is sorely needed to gather different data representations developed in the context of medical research, interoperability of clinical care software, imaging, and --omics analysis into a coherent, unified data model. Our work identifies this need and presents our experience and a list of actionable lessons learned for future work in this direction.},
  keywords = {Data model,Federated learning,Healthcare,Lessons learned,Medical research,Omics},
  file = {/Users/dkapitan/Zotero/storage/C5RQXIRH/Cremonesi et al. - 2023 - The need for multimodal health data modeling A pr.pdf;/Users/dkapitan/Zotero/storage/K2A9EKFC/S153204642300059X.html}
}

@article{curry2016big,
  title = {The Big Data Value Chain: Definitions, Concepts, and Theoretical Approaches},
  shorttitle = {The Big Data Value Chain},
  author = {Curry, Edward},
  year = {2016},
  journal = {New horizons for a data-driven economy: A roadmap for usage and exploitation of big data in Europe},
  pages = {29--37},
  publisher = {Springer International Publishing},
  urldate = {2024-05-27},
  file = {/Users/dkapitan/Zotero/storage/F78VAX3X/Curry - 2016 - The big data value chain definitions, concepts, a.pdf}
}

@incollection{curry2021reference,
  title = {A {{Reference Model}} for {{Big Data Technologies}}},
  booktitle = {The {{Elements}} of {{Big Data Value}}: {{Foundations}} of the {{Research}} and {{Innovation Ecosystem}}},
  author = {Curry, Edward and Metzger, Andreas and Berre, Arne J. and Monz{\'o}n, Andr{\'e}s and {Boggio-Marzet}, Alessandra},
  editor = {Curry, Edward and Metzger, Andreas and Zillner, Sonja and Pazzaglia, Jean-Christophe and Garc{\'i}a Robles, Ana},
  year = {2021},
  pages = {127--151},
  publisher = {Springer International Publishing},
  address = {Cham},
  doi = {10.1007/978-3-030-68176-0_6},
  urldate = {2024-01-11},
  abstract = {The Big Data Value (BDV) Reference Model has been developed with input from technical experts and stakeholders along the whole big data value chain. The BDV Reference Model may serve as a common reference framework to locate big data technologies on the overall IT stack. It addresses the main technical concerns and aspects to be considered for big data value systems. The BDV Reference Model enables the mapping of existing and future data technologies within a common framework. Within this chapter, we detail the reference model in more detail and show how it can be used to manage a portfolio of research and innovation projects.},
  isbn = {978-3-030-68176-0},
  langid = {english},
  keywords = {Big data technologies,Data analysis,Data management,Data processing,Data protection,Data visualisation,Reference model},
  file = {/Users/dkapitan/Zotero/storage/3HMH2BE9/Curry et al. - 2021 - A Reference Model for Big Data Technologies.pdf}
}

@article{dalhatu2023paper,
  title = {From {{Paper Files}} to {{Web-Based Application}} for {{Data-Driven Monitoring}} of {{HIV Programs}}: {{Nigeria}}'s {{Journey}} to a {{National Data Repository}} for {{Decision-Making}} and {{Patient Care}}},
  shorttitle = {From {{Paper Files}} to {{Web-Based Application}} for {{Data-Driven Monitoring}} of {{HIV Programs}}},
  author = {Dalhatu, Ibrahim and Aniekwe, Chinedu and Bashorun, Adebobola and Abdulkadir, Alhassan and Dirlikov, Emilio and Ohakanu, Stephen and Adedokun, Oluwasanmi and Oladipo, Ademola and Jahun, Ibrahim and Murie, Lisa and Yoon, Steven and {Abdu-Aguye}, Mubarak G. and Sylvanus, Ahmed and Indyer, Samuel and Abbas, Isah and Bello, Mustapha and Nalda, Nannim and Alagi, Matthias and Odafe, Solomon and Adebajo, Sylvia and Ogorry, Otse and Akpu, Murphy and Okoye, Ifeanyi and Kakanfo, Kunle and Onovo, Amobi Andrew and Ashefor, Gregory and Nzelu, Charles and Ikpeazu, Akudo and Aliyu, Gambo and Ellerbrock, Tedd and Boyd, Mary and Stafford, Kristen A. and Swaminathan, Mahesh},
  year = {2023},
  month = sep,
  journal = {Methods of Information in Medicine},
  volume = {62},
  number = {03/04},
  pages = {130--139},
  issn = {0026-1270, 2511-705X},
  doi = {10.1055/s-0043-1768711},
  urldate = {2024-03-25},
  abstract = {Abstract             Background{$\quad$}Timely and reliable data are crucial for clinical, epidemiologic, and program management decision making. Electronic health information systems provide platforms for managing large longitudinal patient records. Nigeria implemented the National Data Repository (NDR) to create a central data warehouse of all people living with human immunodeficiency virus (PLHIV) while providing useful functionalities to aid decision making at different levels of program implementation.             Objective{$\quad$}We describe the Nigeria NDR and its development process, including its use for surveillance, research, and national HIV program monitoring toward achieving HIV epidemic control.             Methods{$\quad$}Stakeholder engagement meetings were held in 2013 to gather information on data elements and vocabulary standards for reporting patient-level information, technical infrastructure, human capacity requirements, and information flow. Findings from these meetings guided the development of the NDR. An implementation guide provided common terminologies and data reporting structures for data exchange between the NDR and the electronic medical record (EMR) systems. Data from the EMR were encoded in extensible markup language and sent to the NDR over secure hypertext transfer protocol after going through a series of validation processes.             Results{$\quad$}By June 30, 2021, the NDR had up-to-date records of 1,477,064 (94.4\%) patients receiving HIV treatment across 1,985 health facilities, of which 1,266,512 (85.7\%) patient records had fingerprint template data to support unique patient identification and record linkage to prevent registration of the same patient under different identities. Data from the NDR was used to support HIV program monitoring, case-based surveillance and production of products like the monthly lists of patients who have treatment interruptions and dashboards for monitoring HIV test and start.             Conclusion{$\quad$}The NDR enabled the availability of reliable and timely data for surveillance, research, and HIV program monitoring to guide program improvements to accelerate progress toward epidemic control.},
  langid = {english},
  file = {/Users/dkapitan/Zotero/storage/TGU3P9XW/Dalhatu et al. - 2023 - From Paper Files to Web-Based Application for Data.pdf}
}

@article{davies2019solidarity,
  title = {Solidarity and {{Responsibility}} in {{Health Care}}},
  author = {Davies, Ben and Savulescu, Julian},
  year = {2019},
  month = jul,
  journal = {Public Health Ethics},
  volume = {12},
  number = {2},
  pages = {133--144},
  issn = {1754-9973},
  doi = {10.1093/phe/phz008},
  urldate = {2024-08-27},
  abstract = {Some healthcare systems are said to be grounded in solidarity because healthcare is funded as a form of mutual support. This article argues that health care systems that are grounded in solidarity have the right to penalise some users who are responsible for their poor health. This derives from the fact that solidary systems involve both rights and obligations and, in some cases, those who avoidably incur health burdens violate obligations of solidarity. Penalties warranted include direct patient contribution to costs, and lower priority treatment, but not typically full exclusion from the healthcare system. We also note two important restrictions on this argument. First, failures of solidary obligations can only be assumed under conditions that are conducive to sufficiently autonomous choice, which occur when patients are given `Golden Opportunities' to improve their health. Second, because poor health does not occur in a social vacuum, an insistence on solidarity as part of healthcare is legitimate only if all members of society are held to similar standards of solidarity. We cannot insist upon, and penalise failures of, solidarity only for those who are unwell, and who cannot afford to evade the terms of public health.},
  pmcid = {PMC6655468},
  pmid = {31384302},
  file = {/Users/dkapitan/Zotero/storage/LIZ46Z7R/Davies and Savulescu - 2019 - Solidarity and Responsibility in Health Care.pdf}
}

@article{dennis2019initiation,
  title = {Initiation and Continuity of Maternal Healthcare: Examining the Role of Vouchers and User-Fee Removal on Maternal Health Service Use in {{Kenya}}},
  shorttitle = {Initiation and Continuity of Maternal Healthcare},
  author = {Dennis, Mardieh L and Benova, Lenka and Abuya, Timothy and Quartagno, Matteo and Bellows, Ben and Campbell, Oona M R},
  year = {2019},
  month = mar,
  journal = {Health Policy and Planning},
  volume = {34},
  number = {2},
  pages = {120--131},
  issn = {0268-1080},
  doi = {10.1093/heapol/czz004},
  urldate = {2024-09-06},
  abstract = {This study explores the relationship between two health financing initiatives on women's progression through the maternal health continuum in Kenya: a subsidized reproductive health voucher programme (2006--16) and the introduction of free maternity services in all government facilities (2013). Using cross-sectional survey data, we ran three multivariable logistic regression models examining the effects of the voucher programme, free maternity policy, health insurance and other determinants on (1) early antenatal care (ANC) initiation (first visit within the first trimester of pregnancy), (2) receiving continuous care (1+ ANC, facility birth, 1+ post-natal care (PNC) check) and (3) completing the maternal health pathway as recommended (4+ ANC, facility birth, 1+ PNC, with first check occurring within 48\,h of delivery). Full implementation of the voucher programme was positively associated with receiving continuous care among users of 1+ ANC [interaction term adjusted odds ratio (aOR): 1.33, P\,=\,0.014]. Early ANC initiation (aOR: 1.32, P\,=\,0.001) and use of private sector ANC (aOR: 1.93, P\,\<\,0.001) were also positively associated with use of continuous care among ANC users. Among continuous care users, early ANC was associated with increased odds of completing the maternal health pathway as recommended (aOR: 3.80, P\,\<\,0.001). Higher parity was negatively associated with all three outcomes, while having health insurance was positively associated with each outcome. The impact of other sociodemographic factors such as maternal age, education, wealth quintile, urban residence, and employment varied by outcome; however, the findings generally suggest that marginalized women faced greater barriers to early ANC initiation and continuity of care. Health financing and women's timing and source of ANC are strongly related to their subsequent progression through the maternal health pathway. To increase continuity of care and improve maternal health outcomes, policymakers must therefore focus on equitably reducing financial and other barriers to care seeking and improving quality of care throughout the continuum.},
  file = {/Users/dkapitan/Zotero/storage/5LXL4Q58/Dennis et al. - 2019 - Initiation and continuity of maternal healthcare .pdf}
}

@article{dennis2020examining,
  title = {Examining User Fee Reductions in Public Primary Healthcare Facilities in {{Kenya}}, 1997--2012: Effects on the Use and Content of Antenatal Care},
  shorttitle = {Examining User Fee Reductions in Public Primary Healthcare Facilities in {{Kenya}}, 1997--2012},
  author = {Dennis, Mardieh L. and Benova, Lenka and Goodman, Catherine and Barasa, Edwine and Abuya, Timothy and Campbell, Oona M. R.},
  year = {2020},
  month = mar,
  journal = {International Journal for Equity in Health},
  volume = {19},
  number = {1},
  pages = {35},
  issn = {1475-9276},
  doi = {10.1186/s12939-020-1150-8},
  urldate = {2024-09-06},
  abstract = {In 2004, The Kenyan government removed user fees in public dispensaries and health centers and replaced them with registration charges of 10 and 20 Kenyan shillings (2004 \$US 0.13 and \$0.25), respectively. This was termed the 10/20 policy. We examined the effect of this policy on the coverage, timing, source, and content of antenatal care (ANC), and the equity in these outcomes.},
  langid = {english},
  keywords = {Antenatal care,Kenya,Maternal health,Medical Ethics,Universal healthcare coverage,User fees},
  file = {/Users/dkapitan/Zotero/storage/CXUWR3TH/Dennis et al. - 2020 - Examining user fee reductions in public primary he.pdf}
}

@article{dereuver2018digital,
  title = {The {{Digital Platform}}: {{A Research Agenda}}},
  shorttitle = {The {{Digital Platform}}},
  author = {{de Reuver}, Mark and S{\o}rensen, Carsten and Basole, Rahul C.},
  year = {2018},
  month = jun,
  journal = {Journal of Information Technology},
  volume = {33},
  number = {2},
  pages = {124--135},
  publisher = {SAGE Publications Ltd},
  issn = {0268-3962},
  doi = {10.1057/s41265-016-0033-3},
  urldate = {2023-02-15},
  abstract = {As digital platforms are transforming almost every industry today, they are slowly finding their way into the mainstream information systems (ISs) literature. Digital platforms are a challenging research object because of their distributed nature and intertwinement with institutions, markets and technologies. New research challenges arise as a result of the exponentially growing scale of platform innovation, the increasing complexity of platform architectures and the spread of digital platforms to many different industries. This paper develops a research agenda for digital platforms research in IS. We recommend researchers seek to (1) advance conceptual clarity by providing clear definitions that specify the unit of analysis, degree of digitality and the sociotechnical nature of digital platforms; (2) define the proper scoping of digital platform concepts by studying platforms on different architectural levels and in different industry settings; and (3) advance methodological rigour by employing embedded case studies, longitudinal studies, design research, data-driven modelling and visualisation techniques. Considering current developments in the business domain, we suggest six questions for further research: (1) Are platforms here to stay? (2) How should platforms be designed? (3) How do digital platforms transform industries? (4) How can data-driven approaches inform digital platforms research? (5) How should researchers develop theory for digital platforms? and (6) How do digital platforms affect everyday life?},
  langid = {english},
  file = {/Users/dkapitan/Zotero/storage/Z2GNA5YA/de Reuver et al. - 2018 - The Digital Platform A Research Agenda.pdf}
}

@inproceedings{dereuver2022openness,
  title = {The Openness of Data Platforms: A Research Agenda},
  shorttitle = {The Openness of Data Platforms},
  booktitle = {Proceedings of the 1st {{International Workshop}} on {{Data Economy}}},
  author = {{de Reuver}, Mark and Ofe, Hosea and Agahari, Wirawan and Abbas, Antragama Ewa and Zuiderwijk, Anneke},
  year = {2022},
  month = dec,
  series = {{{DE}} '22},
  pages = {34--41},
  publisher = {Association for Computing Machinery},
  address = {New York, NY, USA},
  doi = {10.1145/3565011.3569056},
  urldate = {2023-02-15},
  abstract = {Data platforms are the keystone of the data economy. When opened up, data platforms allow data owners, data consumers and third parties to interact. Yet, openness may also harm business and societal interests. Literature on platform openness does not cover data platforms, and data economy scholars rarely study platform openness. Therefore, this paper develops a research agenda on the openness of data platforms. We explore how data platforms differ from conventional digital platforms (e.g., software platforms). From those differentiating characteristics, we identify areas for future work: (1) The specific characteristics of data require reconceptualizing the object of platform openness; (2) New ways in which data platforms can be opened should be conceptualized; (3) As data platforms are tailored to specific industries, platform-to-platform openness should be a novel unit of analysis; (4) Because opening up data platforms create novel risks, new reasons to (not) open up data platforms should be studied.},
  isbn = {978-1-4503-9923-4},
  keywords = {data ecosystem,data marketplace,data platform,platform openness},
  file = {/Users/dkapitan/Zotero/storage/CSL6NCAX/de Reuver et al. - 2022 - The openness of data platforms a research agenda.pdf}
}

@misc{designinga,
  title = {Designing and {{Evaluating Control Mechanisms}} for {{Sovereign Data Sharing}} through a {{Meta-Platform}} for {{Data Marketplaces}} {\textbar} {{TU Delft Repository}}},
  urldate = {2024-08-14},
  howpublished = {https://repository.tudelft.nl/record/uuid:3bc77a9e-7912-4b79-9e86-d0cc3c526785},
  file = {/Users/dkapitan/Zotero/storage/HRK82E2I/uuid3bc77a9e-7912-4b79-9e86-d0cc3c526785.html}
}

@misc{developing,
  title = {Developing {{A Semantic Web-based Framework}} for {{Executing}} the {{Clinical Quality Language Using FHIR}} - -},
  urldate = {2024-05-27},
  howpublished = {https://bia.unibz.it/esploro/outputs/conferenceProceeding/Developing-A-Semantic-Web-based-Framework-for-Executing-the-Clinical-Quality-Language-Using-FHIR/991005772984901241}
}

@misc{digitalpublicgoods,
  title = {Digital {{Public Goods Alliance}}},
  year = {2024},
  journal = {Digital Public Goods Alliance - Promoting digital public goods to create a more equitable world},
  urldate = {2024-02-05},
  abstract = {Unlocking the potential of open-source technologies for a more equitable world. Explore and learn more about digital public goods The Digital Public Goods Alliance is a multi-stakeholder initiative that accelerates the attainment of the sustainable development goals by facilitating the discovery, development, use of, and investment in digital public goods. Learn More},
  howpublished = {https://digitalpublicgoods.net/},
  file = {/Users/dkapitan/Zotero/storage/J5Y9ZM7S/digitalpublicgoods.net.html}
}

@misc{digitalsquare2020instantopenhie,
  title = {Advancing {{Instant OpenHIE}} {\textbar} {{Digital Square Open Application Platform}}},
  urldate = {2024-04-02},
  howpublished = {https://applications.digitalsquare.io/content/advancing-instant-openhie},
  file = {/Users/dkapitan/Zotero/storage/JYDLLP35/advancing-instant-openhie.html}
}

@article{dohmen2022implementing,
  title = {Implementing Value-Based Healthcare Using a Digital Health Exchange Platform to Improve Pregnancy and Childbirth Outcomes in Urban and Rural {{Kenya}}},
  author = {Dohmen, Peter and De Sanctis, Teresa and Waiyaiya, Emma and Janssens, Wendy and {Rinke de Wit}, Tobias and Spieker, Nicole and {Van der Graaf}, Mark and Van Raaij, Erik M.},
  year = {2022},
  month = nov,
  journal = {Frontiers in Public Health},
  volume = {10},
  publisher = {Frontiers},
  issn = {2296-2565},
  doi = {10.3389/fpubh.2022.1040094},
  urldate = {2024-09-06},
  abstract = {{$<$}p{$>$}Maternal and neonatal mortality rates in many low- and middle-income countries (LMICs) are still far above the targets of the United Nations Sustainable Development Goal 3. Value-based healthcare (VBHC) has the potential to outperform traditional supply-driven approaches in changing this dismal situation, and significantly improve maternal, neonatal and child health (MNCH) outcomes. We developed a theory of change and used a cohort-based implementation approach to create short and long learning cycles along which different components of the VBHC framework were introduced and evaluated in Kenya. At the core of the approach was a value-based care bundle for maternity care, with predefined cost and quality of care using WHO guidelines and adjusted to the risk profile of the pregnancy. The care bundle was implemented using a digital exchange platform that connects pregnant women, clinics and payers. The platform manages financial transactions, enables bi-directional communication with pregnant women {$<$}italic{$>$}via{$<$}/italic{$>$} SMS, collects data from clinics and shares enriched information {$<$}italic{$>$}via{$<$}/italic{$>$} dashboards with payers and clinics. While the evaluation of health outcomes is ongoing, first results show improved adherence to evidence-based care pathways at a predictable cost per enrolled person. This community case study shows that implementation of the VBHC framework in an LMIC setting is possible for MNCH. The incremental, cohort-based approach enabled iterative learning processes. This can support the restructuring of health systems in low resource settings from an output-driven model to a value based financing-driven model.{$<$}/p{$>$}},
  langid = {english},
  keywords = {cohort-based implementation,Digital Health,LMIC,MNCH,Outcome measurement,value-based healthcare (VBHC)},
  file = {/Users/dkapitan/Zotero/storage/CV4DD939/Dohmen et al. - 2022 - Implementing value-based healthcare using a digita.pdf}
}

@inproceedings{duboc2006framework,
  title = {A Framework for Modelling and Analysis of Software Systems Scalability},
  booktitle = {Proceedings of the 28th International Conference on {{Software}} Engineering},
  author = {Duboc, Leticia and Rosenblum, David S. and Wicks, Tony},
  year = {2006},
  month = may,
  pages = {949--952},
  publisher = {ACM},
  address = {Shanghai China},
  doi = {10.1145/1134285.1134460},
  urldate = {2024-01-08},
  abstract = {The term scalability appears frequently in computing literature, but it is a term that is poorly defined and poorly understood. The lack of a clear, consistent and systematic treatment of scalability makes it difficult to evaluate claims of scalability and to compare claims from different sources. This paper presents a framework for precisely characterizing and analyzing the scalability of a software system. The framework treats scalability as a multi-criteria optimization problem and captures the dependency relationships that underlie typical notions of scalability. The paper presents the results of a case study in which the framework and analysis method were applied to a real-world system, demonstrating that it is possible to develop a precise, systematic characterization of scalability and to use the characterization to compare the scalability of alternative system designs.},
  isbn = {978-1-59593-375-1},
  langid = {english},
  file = {/Users/dkapitan/Zotero/storage/CC3EVCNW/Duboc et al. - 2006 - A framework for modelling and analysis of software.pdf}
}

@article{duda2022hl7,
  title = {{{HL7 FHIR-based}} Tools and Initiatives to Support Clinical Research: A Scoping Review},
  shorttitle = {{{HL7 FHIR-based}} Tools and Initiatives to Support Clinical Research},
  author = {Duda, Stephany N and Kennedy, Nan and Conway, Douglas and Cheng, Alex C and Nguyen, Viet and {Zayas-Cab{\'a}n}, Teresa and Harris, Paul A},
  year = {2022},
  month = sep,
  journal = {Journal of the American Medical Informatics Association},
  volume = {29},
  number = {9},
  pages = {1642--1653},
  issn = {1527-974X},
  doi = {10.1093/jamia/ocac105},
  urldate = {2023-01-20},
  abstract = {The HL7{\textregistered} fast healthcare interoperability resources (FHIR{\textregistered}) specification has emerged as the leading interoperability standard for the exchange of healthcare data. We conducted a scoping review to identify trends and gaps in the use of FHIR for clinical research.We reviewed published literature, federally funded project databases, application websites, and other sources to discover FHIR-based papers, projects, and tools (collectively, ``FHIR projects'') available to support clinical research activities.Our search identified 203 different FHIR projects applicable to clinical research. Most were associated with preparations to conduct research, such as data mapping to and from FHIR formats (n\,=\,66, 32.5\%) and managing ontologies with FHIR (n\,=\,30, 14.8\%), or post-study data activities, such as sharing data using repositories or registries (n\,=\,24, 11.8\%), general research data sharing (n\,=\,23, 11.3\%), and management of genomic data (n\,=\,21, 10.3\%). With the exception of phenotyping (n\,=\,19, 9.4\%), fewer FHIR-based projects focused on needs within the clinical research process itself.Funding and usage of FHIR-enabled solutions for research are expanding, but most projects appear focused on establishing data pipelines and linking clinical systems such as electronic health records, patient-facing data systems, and registries, possibly due to the relative newness of FHIR and the incentives for FHIR integration in health information systems. Fewer FHIR projects were associated with research-only activities.The FHIR standard is becoming an essential component of the clinical research enterprise. To develop FHIR's full potential for clinical research, funding and operational stakeholders should address gaps in FHIR-based research tools and methods.},
  file = {/Users/dkapitan/Zotero/storage/J4EIBEFS/Duda et al. - 2022 - HL7 FHIR-based tools and initiatives to support cl.pdf;/Users/dkapitan/Zotero/storage/5P3NTBII/6639865.html}
}

@article{dunn2023cloudbased,
  title = {A Cloud-Based Pipeline for Analysis of {{FHIR}} and Long-Read Data},
  author = {Dunn, Tim and Cosgun, Erdal},
  year = {2023},
  month = jan,
  journal = {Bioinformatics Advances},
  volume = {3},
  number = {1},
  pages = {vbac095},
  issn = {2635-0041},
  doi = {10.1093/bioadv/vbac095},
  urldate = {2024-01-09},
  abstract = {As genome sequencing becomes cheaper and more accurate, it is becoming increasingly viable to merge this data with electronic health information to inform clinical decisions.In this work, we demonstrate a full pipeline for working with both PacBio sequencing data and clinical FHIR{\textregistered} data, from initial data to tertiary analysis. The electronic health records are stored in FHIR{\textregistered} (Fast Healthcare Interoperability Resource) format, the current leading standard for healthcare data exchange. For the genomic data, we perform variant calling on long-read PacBio HiFi data using Cromwell on Azure. Both data formats are parsed, processed and merged in a single scalable pipeline which securely performs tertiary analyses using cloud-based Jupyter notebooks. We include three example applications: exporting patient information to a database, clustering patients and performing a simple pharmacogenomic study.https://github.com/microsoft/genomicsnotebook/tree/main/fhirgenomicsSupplementary data are available at Bioinformatics Advances online.},
  file = {/Users/dkapitan/Zotero/storage/KM764DPM/Dunn and Cosgun - 2023 - A cloud-based pipeline for analysis of FHIR and lo.pdf;/Users/dkapitan/Zotero/storage/IZSXRU2N/6994207.html}
}

@inproceedings{eapen2019drishti,
  title = {Drishti: {{A Sense-Plan-Act Extension}} to {{Open mHealth Framework Using FHIR}}},
  shorttitle = {Drishti},
  booktitle = {2019 {{IEEE}}/{{ACM}} 1st {{International Workshop}} on {{Software Engineering}} for {{Healthcare}} ({{SEH}})},
  author = {Eapen, Bell Raj and Archer, Norm and Sartipi, Kamran and Yuan, Yufei},
  year = {2019},
  month = may,
  pages = {49--52},
  doi = {10.1109/SEH.2019.00016},
  urldate = {2024-04-15},
  abstract = {Mobile Health (mHealth) is vital in promoting a collaborative healthcare model. Disparate mHealth Apps that do not talk to each other make complex behavioural interventions difficult. Open mHealth is a schema and framework for facilitating health information exchange for mHealth apps. We propose an extension to open mHealth for behavioural interventions. We call our proposed extension; Drishti (yogic gaze). It applies the sense-plan-act paradigm from robotics. We offer an open-source implementation of Drishti, and we evaluate it using a design science research framework.},
  keywords = {Biomedical monitoring,Data models,FHIR,Information systems,Interoperability,Medical services,mHealth,Monitoring,Open source software,Standards},
  file = {/Users/dkapitan/Zotero/storage/WD3XPBNG/Eapen et al. - 2019 - Drishti A Sense-Plan-Act Extension to Open mHealt.pdf;/Users/dkapitan/Zotero/storage/G4YJ9C33/8823907.html}
}

@article{ellis2022science,
  title = {The {{Science}} of {{Learning Health Systems}}: {{Scoping Review}} of {{Empirical Research}}},
  shorttitle = {The {{Science}} of {{Learning Health Systems}}},
  author = {Ellis, Louise A. and Sarkies, Mitchell and Churruca, Kate and Dammery, Genevieve and Meulenbroeks, Isabelle and Smith, Carolynn L. and Pomare, Chiara and Mahmoud, Zeyad and Zurynski, Yvonne and Braithwaite, Jeffrey},
  year = {2022},
  month = feb,
  journal = {JMIR Medical Informatics},
  volume = {10},
  number = {2},
  pages = {e34907},
  publisher = {JMIR Publications Inc., Toronto, Canada},
  doi = {10.2196/34907},
  urldate = {2024-09-06},
  abstract = {Background: The development and adoption of a learning health system (LHS) has been proposed as a means to address key challenges facing current and future health care systems. The first review of the LHS literature was conducted 5 years ago, identifying only a small number of published papers that had empirically examined the implementation or testing of an LHS. It is timely to look more closely at the published empirical research and to ask the question, Where are we now? 5 years on from that early LHS review. Objective: This study performed a scoping review of empirical research within the LHS domain. Taking an ``implementation science'' lens, the review aims to map out the empirical research that has been conducted to date, identify limitations, and identify future directions for the field. Methods: Two academic databases (PubMed and Scopus) were searched using the terms ``learning health* system*'' for papers published between January 1, 2016, to January 31, 2021, that had an explicit empirical focus on LHSs. Study information was extracted relevant to the review objective, including each study's publication details; primary concern or focus; context; design; data type; implementation framework, model, or theory used; and implementation determinants or outcomes examined. Results: A total of 76 studies were included in this review. Over two-thirds of the studies were concerned with implementing a particular program, system, or platform (53/76, 69.7\%) designed to contribute to achieving an LHS. Most of these studies focused on a particular clinical context or patient population (37/53, 69.8\%), with far fewer studies focusing on whole hospital systems (4/53, 7.5\%) or on other broad health care systems encompassing multiple facilities (12/53, 22.6\%). Over two-thirds of the program-specific studies utilized quantitative methods (37/53, 69.8\%), with a smaller number utilizing qualitative methods (10/53, 18.9\%) or mixed-methods designs (6/53, 11.3\%). The remaining 23 studies were classified into 1 of 3 key areas: ethics, policies, and governance (10/76, 13.2\%); stakeholder perspectives of LHSs (5/76, 6.6\%); or LHS-specific research strategies and tools (8/76, 10.5\%). Overall, relatively few studies were identified that incorporated an implementation science framework. Conclusions: Although there has been considerable growth in empirical applications of LHSs within the past 5 years, paralleling the recent emergence of LHS-specific research strategies and tools, there are few high-quality studies. Comprehensive reporting of implementation and evaluation efforts is an important step to moving the LHS field forward. In particular, the routine use of implementation determinant and outcome frameworks will improve the assessment and reporting of barriers, enablers, and implementation outcomes in this field and will enable comparison and identification of trends across studies.},
  copyright = {This is an open-access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work, first published JMIR Medical Informatics, is properly cited. The complete bibliographic information, a link to the original publication on https://medinform.jmir.org/, as well as this copyright and license information must be included.},
  langid = {english},
  file = {/Users/dkapitan/Zotero/storage/8PVX6BB3/Ellis et al. - 2022 - The Science of Learning Health Systems Scoping Re.pdf;/Users/dkapitan/Zotero/storage/755MG97Z/e34907.html}
}

@article{enticott2021learning,
  title = {Learning Health Systems Using Data to Drive Healthcare Improvement and Impact: A Systematic Review},
  shorttitle = {Learning Health Systems Using Data to Drive Healthcare Improvement and Impact},
  author = {Enticott, Joanne and Johnson, Alison and Teede, Helena},
  year = {2021},
  month = mar,
  journal = {BMC Health Services Research},
  volume = {21},
  number = {1},
  pages = {200},
  issn = {1472-6963},
  doi = {10.1186/s12913-021-06215-8},
  urldate = {2024-09-06},
  abstract = {The transition to electronic health records offers the potential for big data to drive the next frontier in healthcare improvement. Yet there are multiple barriers to harnessing the power of data. The Learning Health System (LHS) has emerged as a model to overcome these barriers, yet there remains limited evidence of impact on delivery or outcomes of healthcare.},
  langid = {english},
  keywords = {Artificial Intelligence,Digital health,Health data hubs,Health services research,Learning health systems},
  file = {/Users/dkapitan/Zotero/storage/E4PZHKRC/Enticott et al. - 2021 - Learning health systems using data to drive health.pdf}
}

@article{evertsz2023what,
  title = {What Constitutes Equitable Data Sharing in Global Health Research? {{A}} Scoping Review of the Literature on Low-Income and Middle-Income Country Stakeholders' Perspectives},
  shorttitle = {What Constitutes Equitable Data Sharing in Global Health Research?},
  author = {Evertsz, Natalia and Bull, Susan and Pratt, Bridget},
  year = {2023},
  month = mar,
  journal = {BMJ Global Health},
  volume = {8},
  number = {3},
  pages = {e010157},
  publisher = {BMJ Specialist Journals},
  issn = {2059-7908},
  doi = {10.1136/bmjgh-2022-010157},
  urldate = {2024-08-26},
  abstract = {Introduction Despite growing consensus on the need for equitable data sharing, there has been very limited discussion about what this should entail in practice. As a matter of procedural fairness and epistemic justice, the perspectives of low-income and middle-income country (LMIC) stakeholders must inform concepts of equitable health research data sharing. This paper investigates published perspectives in relation to how equitable data sharing in global health research should be understood. Methods We undertook a scoping review (2015 onwards) of the literature on LMIC stakeholders' experiences and perspectives of data sharing in global health research and thematically analysed the 26 articles included in the review. Results We report LMIC stakeholders' published views on how current data sharing mandates may exacerbate inequities, what structural changes are required in order to create an environment conducive to equitable data sharing and what should comprise equitable data sharing in global health research. Conclusions In light of our findings, we conclude that data sharing under existing mandates to share data (with minimal restrictions) risks perpetuating a neocolonial dynamic. To achieve equitable data sharing, adopting best practices in data sharing is necessary but insufficient. Structural inequalities in global health research must also be addressed. It is thus imperative that the structural changes needed to ensure equitable data sharing are incorporated into the broader dialogue on global health research.},
  chapter = {Original research},
  copyright = {{\copyright} Author(s) (or their employer(s)) 2023. Re-use permitted under CC BY. Published by BMJ.. https://creativecommons.org/licenses/by/4.0/This is an open access article distributed in accordance with the Creative Commons Attribution 4.0 Unported (CC BY 4.0) license, which permits others to copy, redistribute, remix, transform and build upon this work for any purpose, provided the original work is properly cited, a link to the licence is given, and indication of whether changes were made. See: https://creativecommons.org/licenses/by/4.0/.},
  langid = {english},
  pmid = {36977523},
  keywords = {Health policies and all other topics,Review},
  file = {/Users/dkapitan/Zotero/storage/6N77WQNA/Evertsz et al. - 2023 - What constitutes equitable data sharing in global .pdf}
}

@inproceedings{fayad2005scalable,
  title = {Towards Scalable and Adaptable Software Architectures},
  booktitle = {{{IRI}} -2005 {{IEEE International Conference}} on {{Information Reuse}} and {{Integration}}, {{Conf}}, 2005.},
  author = {Fayad, M.E. and Hamza, H.S. and Sanchez, H.A.},
  year = {2005},
  pages = {102--107},
  publisher = {IEEE},
  address = {Las Vegas, NV, USA},
  doi = {10.1109/IRI-05.2005.1506457},
  urldate = {2024-01-08},
  abstract = {Developing scalable and adaptable architectures that can accommodate evolving changes is crucial for reducing software development cost. To achieve scalability and adaptability, developers should be able to identify where and how new (current) layers will be added (removed) from the architecture. Failing to do so may lead to software architectures that require a considerable modifications when the system evolves or changes due to new or added requirements. In this paper, we address the problem of developing scalable software architectures that can accommodate new and/or modified requirements without the need for re-developing the architecture from scratch. The approach is demonstrated through a case study.},
  isbn = {978-0-7803-9093-5},
  langid = {english},
  file = {/Users/dkapitan/Zotero/storage/B37NRBNR/Fayad et al. - 2005 - Towards scalable and adaptable software architectu.pdf}
}

@article{fiksel2003designing,
  title = {Designing {{Resilient}}, {{Sustainable Systems}}},
  author = {Fiksel, Joseph},
  year = {2003},
  month = dec,
  journal = {Environmental Science \& Technology},
  volume = {37},
  number = {23},
  pages = {5330--5339},
  publisher = {American Chemical Society},
  issn = {0013-936X},
  doi = {10.1021/es0344819},
  urldate = {2024-08-13},
  abstract = {Pursuit of sustainable development requires a systems approach to the design of industrial product and service systems. Although many business enterprises have adopted sustainability goals, the actual development of sustainable systems remains challenging because of the broad range of economic, environmental and social factors that need to be considered across the system life cycle. Traditional systems engineering practices try to anticipate and resist disruptions but may be vulnerable to unforeseen factors. An alternative is to design systems with inherent ``resilience'' by taking advantage of fundamental properties such as diversity, efficiency, adaptability, and cohesion. Previous work on sustainable design has focused largely upon ecological efficiency improvements. For example, companies have found that reducing material and energy intensity and converting wastes into valuable secondary products creates value for shareholders as well as for society at large. To encourage broader systems thinking, a design protocol is presented that involves the following steps:\, identifying system function and boundaries, establishing requirements, selecting appropriate technologies, developing a system design, evaluating anticipated performance, and devising a practical means for system deployment. The approach encourages explicit consideration of resilience in both engineered systems and the larger systems in which they are embedded.},
  file = {/Users/dkapitan/Zotero/storage/6UYW9XX4/Fiksel - 2003 - Designing Resilient, Sustainable Systems.pdf}
}

@article{fishenden2013digital,
  title = {Digital {{Government}}, {{Open Architecture}}, and {{Innovation}}: {{Why Public Sector IT Will Never Be}} the {{Same Again}}},
  shorttitle = {Digital {{Government}}, {{Open Architecture}}, and {{Innovation}}},
  author = {Fishenden, Jerry and Thompson, Mark},
  year = {2013},
  month = oct,
  journal = {Journal of Public Administration Research and Theory},
  volume = {23},
  number = {4},
  pages = {977--1004},
  issn = {1053-1858},
  doi = {10.1093/jopart/mus022},
  urldate = {2024-08-12},
  abstract = {This article argues that the future of public services will be shaped increasingly by the evolution of global, Internet-enabled, digital platforms, with two distinctive technical and commercial features. First, use of open standards and architectures that separate standard business logic from supporting applications will allow government to become technology- and vendor-agnostic, freeing it from its overdependence on proprietary systems and suppliers. Second, over time, open standards and increased market choice will drive both innovation and progressive convergence on cheaper, standard ``utility'' public services. These two features will combine to create a powerful dynamic situation, driving disintegration of traditional ``black boxed'' technologies and services, traditionally organized around ``systems integrators'' and departmental structures, and their reaggregation around the citizen in the form of services. Such reaggregation is allowing progressively sharp distinctions between niche/innovative and commodity/standard offerings, supplied by a plural, innovative, and more cost-effective marketplace, with unprecedented implications for the way in which the state buys and deploys technology. We draw on a range of data from across public and private sectors to illustrate our argument and identify some key policy and implementation recommendations.},
  file = {/Users/dkapitan/Zotero/storage/5QBGHW5N/Fishenden and Thompson - 2013 - Digital Government, Open Architecture, and Innovation Why Public Sector IT Will Never Be the Same A.pdf}
}

@misc{flaskmultipass,
  title = {Flask-{{Multipass}} --- {{Flask-Multipass}} 0.5.3 Documentation},
  urldate = {2024-02-09},
  howpublished = {https://flask-multipass.readthedocs.io/en/latest/}
}

@article{friedman2015science,
  title = {Toward a Science of Learning Systems: A Research Agenda for the High-Functioning {{Learning Health System}}},
  shorttitle = {Toward a Science of Learning Systems},
  author = {Friedman, Charles and Rubin, Joshua and Brown, Jeffrey and Buntin, Melinda and Corn, Milton and Etheredge, Lynn and Gunter, Carl and Musen, Mark and Platt, Richard and Stead, William and Sullivan, Kevin and Van Houweling, Douglas},
  year = {2015},
  month = jan,
  journal = {Journal of the American Medical Informatics Association},
  volume = {22},
  number = {1},
  pages = {43--50},
  issn = {1067-5027},
  doi = {10.1136/amiajnl-2014-002977},
  urldate = {2024-09-06},
  abstract = {Objective The capability to share data, and harness its potential to generate knowledge rapidly and inform decisions, can have transformative effects that improve health. The infrastructure to achieve this goal at scale---marrying technology, process, and policy---is commonly referred to as the Learning Health System (LHS). Achieving an LHS raises numerous scientific challenges.Materials and methods The National Science Foundation convened an invitational workshop to identify the fundamental scientific and engineering research challenges to achieving a national-scale LHS. The workshop was planned by a 12-member committee and ultimately engaged 45 prominent researchers spanning multiple disciplines over 2\>days in Washington, DC on 11--12 April 2013.Results The workshop participants collectively identified 106 research questions organized around four system-level requirements that a high-functioning LHS must satisfy. The workshop participants also identified a new cross-disciplinary integrative science of cyber-social ecosystems that will be required to address these challenges.Conclusions The intellectual merit and potential broad impacts of the innovations that will be driven by investments in an LHS are of great potential significance. The specific research questions that emerged from the workshop, alongside the potential for diverse communities to assemble to address them through a `new science of learning systems', create an important agenda for informatics and related disciplines.},
  file = {/Users/dkapitan/Zotero/storage/DXA48GJF/Friedman et al. - 2015 - Toward a science of learning systems a research a.pdf}
}

@misc{full,
  title = {Full Article: {{Comparative}} Assessment of the Human and Animal Health Surveillance Systems in {{Tanzania}}: {{Opportunities}} for an Integrated One Health Surveillance Platform},
  urldate = {2024-04-16},
  howpublished = {https://www-tandfonline-com.dianus.libr.tue.nl/doi/full/10.1080/17441692.2022.2110921},
  file = {/Users/dkapitan/Zotero/storage/ZE8B6CIN/17441692.2022.html}
}

@article{gamal2021integrated,
  title = {Integrated {{Document-based Electronic Health Records Persistence Framework}}},
  author = {Gamal, Aya and Barakat, Sherif and Rezk, Amira},
  year = {2021},
  journal = {International Journal of Advanced Computer Science and Applications},
  volume = {12},
  number = {10},
  issn = {21565570, 2158107X},
  doi = {10.14569/IJACSA.2021.0121017},
  urldate = {2024-04-15},
  abstract = {Electronic health record systems work beyond just recording patients` health data. They have multiple secondary functionalities, such as data reporting and clinical decision support. As each of these systems` workloads has contradictory different needs, managing a multipurpose electronic health record is a challenge. This paper proposes a unified healthcare data framework that can simplify health information system infrastructure. It investigates the suitability of the documentbased NoSQL persistence mechanism, storing electronic health records data as a design choice for managing varied complexity ad hoc queries used in operational business intelligence. The performance of the most popular two document-based NoSQL back-ends, Couchbase Server and MongoDB, is compared according to the size of the database and query execution time. Results showed that while MongoDB can execute simple singledocument queries nearly in milliseconds. It does not provide satisfactory response time for unplanned complex queries spanning multiple documents. By utilizing its analytics services and multi-dimensional scaling architecture, Couchbase Server multi-node cluster outperforms the response times of MongoDB for both simple and complex healthcare data access patterns. The primary advantage of the proposed tightly coupled EHRs processing framework is its flexibility to manage workload according to changing requirements.},
  langid = {english},
  file = {/Users/dkapitan/Zotero/storage/DL8MWP8Z/Gamal et al. - 2021 - Integrated Document-based Electronic Health Record.pdf}
}

@article{garzarelli2008open,
  title = {Open Source Software and Economic Growth: {{A}} Classical Division of Labor Perspective},
  shorttitle = {Open Source Software and Economic Growth},
  author = {Garzarelli, Giampaolo and Limam, Yasmina Reem and Thomassen, Bj{\o}rn},
  year = {2008},
  month = apr,
  journal = {Information Technology for Development},
  volume = {14},
  number = {2},
  pages = {116--135},
  issn = {0268-1102, 1554-0170},
  doi = {10.1002/itdj.20092},
  urldate = {2024-08-28},
  langid = {english},
  file = {/Users/dkapitan/Zotero/storage/GSEJD7C9/Garzarelli et al. - 2008 - Open source software and economic growth A classi.pdf}
}

@article{gebreslassie2023fhir4fair,
  title = {{{FHIR4FAIR}}: {{Leveraging FHIR}} in Health Data {{FAIRfication}} Process: {{In}} the Case of {{VODAN-A}}},
  shorttitle = {{{FHIR4FAIR}}},
  author = {Gebreslassie, Tesfit Gebremeskel and {van Reisen}, Mirjam and Amare, Samson Yohannes and Taye, Getu Tadele and Plug, Ruduan},
  year = {2023},
  month = jan,
  journal = {FAIR Connect},
  volume = {1},
  number = {1},
  pages = {49--54},
  publisher = {IOS Press},
  doi = {10.3233/FC-230504},
  urldate = {2023-07-03},
  abstract = {This article describes FHIR as a healthcare data exchange standard to attain the FAIR data principles taking the VODAN-A implementation as a showcase. FHIR relies upon the basic unit ``resources'' and the interaction among them. A new FAIR enabling arc},
  langid = {english},
  file = {/Users/dkapitan/Zotero/storage/5C3N39JI/Gebreslassie et al. - 2023 - FHIR4FAIR Leveraging FHIR in health data FAIRfica.pdf}
}

@article{gillwaldfinal,
  title = {Final Report Prepared By:},
  author = {Gillwald, Alison and Johnson, David and Cloete, Laurens and Hadzic, Senka and Kiden, Sarah and Rens, Andrew and Phokeer, Amreesh},
  abstract = {This study analyses the progress, challenges and opportunities of open-source digital infrastructure in Africa. The African continent has seen some rapid progress over the past two decades in areas such as mobile connectivity, electrification and availability of internet-capable devices such as smartphones. However, despite this progress, many African countries remain poor, are vulnerable to shocks such as natural disasters and pandemics, and face various development challenges. As the world becomes more digital, Africa's development is increasingly determined by its digital capability. Open-source digital infrastructure is a key component of the required digital capability. The optimal application of digital infrastructure to development in Africa requires active participation in the creation and maintenance of open-source digital infrastructure contribution, in a manner similar to which research and development enables adoption of technology produced elsewhere through increased absorptive capacity.},
  langid = {english},
  file = {/Users/dkapitan/Zotero/storage/LRHT834N/Gillwald et al. - Final report prepared by.pdf}
}

@article{granger2021jupyter,
  title = {Jupyter: {{Thinking}} and {{Storytelling With Code}} and {{Data}}},
  shorttitle = {Jupyter},
  author = {Granger, Brian E. and Perez, Fernando},
  year = {2021},
  month = mar,
  journal = {Computing in Science \& Engineering},
  volume = {23},
  number = {2},
  pages = {7--14},
  issn = {1521-9615, 1558-366X},
  doi = {10.1109/MCSE.2021.3059263},
  urldate = {2024-03-25},
  langid = {english},
  file = {/Users/dkapitan/Zotero/storage/7TJVD5TE/Granger and Perez - 2021 - Jupyter Thinking and Storytelling With Code and D.pdf}
}

@article{grimes2022pathling,
  title = {Pathling: Analytics on {{FHIR}}},
  shorttitle = {Pathling},
  author = {Grimes, John and Szul, Piotr and {Metke-Jimenez}, Alejandro and Lawley, Michael and Loi, Kylynn},
  year = {2022},
  month = sep,
  journal = {Journal of Biomedical Semantics},
  volume = {13},
  number = {1},
  pages = {23},
  issn = {2041-1480},
  doi = {10.1186/s13326-022-00277-1},
  urldate = {2022-12-07},
  abstract = {Health data analytics is an area that is facing rapid change due to the acceleration of digitization of the health sector, and the changing landscape of health data and clinical terminology standards. Our research has identified a need for improved tooling to support analytics users in the task of analyzing Fast Healthcare Interoperability Resources (FHIR{\textregistered}) data and associated clinical terminology.},
  keywords = {Clinical terminology,Data analytics,FHIR,FHIRPath,Interoperability,SNOMED CT},
  file = {/Users/dkapitan/Zotero/storage/IF28HUHK/Grimes et al. - 2022 - Pathling analytics on FHIR.pdf;/Users/dkapitan/Zotero/storage/PK3Z9NJM/s13326-022-00277-1.html}
}

@article{gruendner2019ketos,
  title = {{{KETOS}}: {{Clinical}} Decision Support and Machine Learning as a Service -- {{A}} Training and Deployment Platform Based on {{Docker}}, {{OMOP-CDM}}, and {{FHIR Web Services}}},
  shorttitle = {{{KETOS}}},
  author = {Gruendner, Julian and Schwachhofer, Thorsten and Sippl, Phillip and Wolf, Nicolas and Erpenbeck, Marcel and Gulden, Christian and Kapsner, Lorenz A. and Zierk, Jakob and Mate, Sebastian and St{\"u}rzl, Michael and Croner, Roland and Prokosch, Hans-Ulrich and Toddenroth, Dennis},
  year = {2019},
  month = oct,
  journal = {PLOS ONE},
  volume = {14},
  number = {10},
  pages = {e0223010},
  publisher = {Public Library of Science},
  issn = {1932-6203},
  doi = {10.1371/journal.pone.0223010},
  urldate = {2024-05-27},
  abstract = {Background and objective To take full advantage of decision support, machine learning, and patient-level prediction models, it is important that models are not only created, but also deployed in a clinical setting. The KETOS platform demonstrated in this work implements a tool for researchers allowing them to perform statistical analyses and deploy resulting models in a secure environment. Methods The proposed system uses Docker virtualization to provide researchers with reproducible data analysis and development environments, accessible via Jupyter Notebook, to perform statistical analysis and develop, train and deploy models based on standardized input data. The platform is built in a modular fashion and interfaces with web services using the Health Level 7 (HL7) Fast Healthcare Interoperability Resources (FHIR) standard to access patient data. In our prototypical implementation we use an OMOP common data model (OMOP-CDM) database. The architecture supports the entire research lifecycle from creating a data analysis environment, retrieving data, and training to final deployment in a hospital setting. Results We evaluated the platform by establishing and deploying an analysis and end user application for hemoglobin reference intervals within the University Hospital Erlangen. To demonstrate the potential of the system to deploy arbitrary models, we loaded a colorectal cancer dataset into an OMOP database and built machine learning models to predict patient outcomes and made them available via a web service. We demonstrated both the integration with FHIR as well as an example end user application. Finally, we integrated the platform with the open source DataSHIELD architecture to allow for distributed privacy preserving data analysis and training across networks of hospitals. Conclusion The KETOS platform takes a novel approach to data analysis, training and deploying decision support models in a hospital or healthcare setting. It does so in a secure and privacy-preserving manner, combining the flexibility of Docker virtualization with the advantages of standardized vocabularies, a widely applied database schema (OMOP-CDM), and a standardized way to exchange medical data (FHIR).},
  langid = {english},
  keywords = {Colorectal cancer,Consortia,Machine learning,Machine learning algorithms,Physicians,Preprocessing,Prototypes,Statistical data},
  file = {/Users/dkapitan/Zotero/storage/RWWQ7PJA/Gruendner et al. - 2019 - KETOS Clinical decision support and machine learn.pdf}
}

@article{gruendner2021framework,
  title = {A {{Framework}} for {{Criteria-Based Selection}} and {{Processing}} of {{Fast Healthcare Interoperability Resources}} ({{FHIR}}) {{Data}} for {{Statistical Analysis}}: {{Design}} and {{Implementation Study}}},
  shorttitle = {A {{Framework}} for {{Criteria-Based Selection}} and {{Processing}} of {{Fast Healthcare Interoperability Resources}} ({{FHIR}}) {{Data}} for {{Statistical Analysis}}},
  author = {Gruendner, Julian and Gulden, Christian and Kampf, Marvin and Mate, Sebastian and Prokosch, Hans-Ulrich and Zierk, Jakob},
  year = {2021},
  month = apr,
  journal = {JMIR Medical Informatics},
  volume = {9},
  number = {4},
  pages = {e25645},
  publisher = {JMIR Publications Inc., Toronto, Canada},
  doi = {10.2196/25645},
  urldate = {2024-05-27},
  abstract = {Background: The harmonization and standardization of digital medical information for research purposes is a challenging and ongoing collaborative effort. Current research data repositories typically require extensive efforts in harmonizing and transforming original clinical data. The Fast Healthcare Interoperability Resources (FHIR) format was designed primarily to represent clinical processes; therefore, it closely resembles the clinical data model and is more widely available across modern electronic health records. However, no common standardized data format is directly suitable for statistical analyses, and data need to be preprocessed before statistical analysis. Objective: This study aimed to elucidate how FHIR data can be queried directly with a preprocessing service and be used for statistical analyses. Methods: We propose that the binary JavaScript Object Notation format of the PostgreSQL (PSQL) open source database is suitable for not only storing FHIR data, but also extending it with preprocessing and filtering services, which directly transform data stored in FHIR format into prepared data subsets for statistical analysis. We specified an interface for this preprocessor, implemented and deployed it at University Hospital Erlangen-N{\"u}rnberg, generated 3 sample data sets, and analyzed the available data. Results: We imported real-world patient data from 2016 to 2018 into a standard PSQL database, generating a dataset of approximately 35.5 million FHIR resources, including ``Patient,'' ``Encounter,'' ``Condition'' (diagnoses specified using International Classification of Diseases codes), ``Procedure,'' and ``Observation'' (laboratory test results). We then integrated the developed preprocessing service with the PSQL database and the locally installed web-based KETOS analysis platform. Advanced statistical analyses were feasible using the developed framework using 3 clinically relevant scenarios (data-driven establishment of hemoglobin reference intervals, assessment of anemia prevalence in patients with cancer, and investigation of the adverse effects of drugs). Conclusions: This study shows how the standard open source database PSQL can be used to store FHIR data and be integrated with a specifically developed preprocessing and analysis framework. This enables dataset generation with advanced medical criteria and the integration of subsequent statistical analysis. The web-based preprocessing service can be deployed locally at the hospital level, protecting patients' privacy while being integrated with existing open source data analysis tools currently being developed across Germany.},
  copyright = {This is an open-access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work, first published JMIR Medical Informatics, is properly cited. The complete bibliographic information, a link to the original publication on https://medinform.jmir.org/, as well as this copyright and license information must be included.},
  langid = {english},
  file = {/Users/dkapitan/Zotero/storage/D2P7B27M/Gruendner et al. - 2021 - A Framework for Criteria-Based Selection and Proce.pdf}
}

@article{gruendner2022architecture,
  title = {The {{Architecture}} of a {{Feasibility Query Portal}} for {{Distributed COVID-19 Fast Healthcare Interoperability Resources}} ({{FHIR}}) {{Patient Data Repositories}}: {{Design}} and {{Implementation Study}}},
  shorttitle = {The {{Architecture}} of a {{Feasibility Query Portal}} for {{Distributed COVID-19 Fast Healthcare Interoperability Resources}} ({{FHIR}}) {{Patient Data Repositories}}},
  author = {Gruendner, Julian and Deppenwiese, Noemi and Folz, Michael and K{\"o}hler, Thomas and Kroll, Bj{\"o}rn and Prokosch, Hans-Ulrich and Rosenau, Lorenz and R{\"u}hle, Mathias and Scheidl, Marc-Anton and Sch{\"u}ttler, Christina and Sedlmayr, Brita and Twrdik, Alexander and Kiel, Alexander and Majeed, Raphael W.},
  year = {2022},
  month = may,
  journal = {JMIR Medical Informatics},
  volume = {10},
  number = {5},
  pages = {e36709},
  publisher = {JMIR Publications Inc., Toronto, Canada},
  doi = {10.2196/36709},
  urldate = {2024-05-27},
  abstract = {Background: An essential step in any medical research project after identifying the research question is to determine if there are sufficient patients available for a study and where to find them. Pursuing digital feasibility queries on available patient data registries has proven to be an excellent way of reusing existing real-world data sources. To support multicentric research, these feasibility queries should be designed and implemented to run across multiple sites and securely access local data. Working across hospitals usually involves working with different data formats and vocabularies. Recently, the Fast Healthcare Interoperability Resources (FHIR) standard was developed by Health Level Seven to address this concern and describe patient data in a standardized format. The Medical Informatics Initiative in Germany has committed to this standard and created data integration centers, which convert existing data into the FHIR format at each hospital. This partially solves the interoperability problem; however, a distributed feasibility query platform for the FHIR standard is still missing. Objective: This study described the design and implementation of the components involved in creating a cross-hospital feasibility query platform for researchers based on FHIR resources. This effort was part of a large COVID-19 data exchange platform and was designed to be scalable for a broad range of patient data. Methods: We analyzed and designed the abstract components necessary for a distributed feasibility query. This included a user interface for creating the query, backend with an ontology and terminology service, middleware for query distribution, and FHIR feasibility query execution service. Results: We implemented the components described in the Methods section. The resulting solution was distributed to 33 German university hospitals. The functionality of the comprehensive network infrastructure was demonstrated using a test data set based on the German Corona Consensus Data Set. A performance test using specifically created synthetic data revealed the applicability of our solution to data sets containing millions of FHIR resources. The solution can be easily deployed across hospitals and supports feasibility queries, combining multiple inclusion and exclusion criteria using standard Health Level Seven query languages such as Clinical Quality Language and FHIR Search. Developing a platform based on multiple microservices allowed us to create an extendable platform and support multiple Health Level Seven query languages and middleware components to allow integration with future directions of the Medical Informatics Initiative. Conclusions: We designed and implemented a feasibility platform for distributed feasibility queries, which works directly on FHIR-formatted data and distributed it across 33 university hospitals in Germany. We showed that developing a feasibility platform directly on the FHIR standard is feasible.},
  copyright = {This is an open-access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work, first published JMIR Medical Informatics, is properly cited. The complete bibliographic information, a link to the original publication on https://medinform.jmir.org/, as well as this copyright and license information must be included.},
  langid = {english},
  file = {/Users/dkapitan/Zotero/storage/JWTLQ68A/Gruendner et al. - 2022 - The Architecture of a Feasibility Query Portal for.pdf}
}

@article{guillot2023fair,
  title = {{{FAIR}} Sharing of Health Data: A Systematic Review of Applicable Solutions},
  shorttitle = {{{FAIR}} Sharing of Health Data},
  author = {Guillot, Paul and B{\o}gsted, Martin and Vesteghem, Charles},
  year = {2023},
  month = nov,
  journal = {Health and Technology},
  volume = {13},
  number = {6},
  pages = {869--882},
  issn = {2190-7196},
  doi = {10.1007/s12553-023-00789-5},
  urldate = {2024-01-23},
  abstract = {Data sharing is essential in health science research. This has also been acknowledged by governments and institutions who have set-up a number of regulations, laws, and initiatives to facilitate it. A large number of initiatives has been trying to address data sharing issues. With the development of the FAIR principles, a set of detailed criteria for evaluating the relevance of such solutions is now available. This article intends to help researchers to choose a suitable solution for sharing their health data in a FAIR way.},
  langid = {english},
  keywords = {Databases Factual,Information Dissemination,Information Storage and Retrieval,Medical Informatics,Metadata},
  file = {/Users/dkapitan/Zotero/storage/I73S2V7R/Guillot et al. - 2023 - FAIR sharing of health data a systematic review o.pdf}
}

@article{hai2023data,
  title = {Data {{Lakes}}: {{A Survey}} of {{Functions}} and {{Systems}}},
  shorttitle = {Data {{Lakes}}},
  author = {Hai, Rihan and Koutras, Christos and Quix, Christoph and Jarke, Matthias},
  year = {2023},
  month = dec,
  journal = {IEEE Transactions on Knowledge and Data Engineering},
  volume = {35},
  number = {12},
  pages = {12571--12590},
  issn = {1558-2191},
  doi = {10.1109/TKDE.2023.3270101},
  urldate = {2024-01-11},
  abstract = {Data lakes are becoming increasingly prevalent for Big Data management and data analytics. In contrast to traditional `schema-on-write' approaches such as data warehouses, data lakes are repositories storing raw data in its original formats and providing a common access interface. Despite the strong interest raised from both academia and industry, there is a large body of ambiguity regarding the definition, functions and available technologies for data lakes. A complete, coherent picture of data lake challenges and solutions is still missing. This survey reviews the development, architectures, and systems of data lakes. We provide a comprehensive overview of research questions for designing and building data lakes. We classify the existing approaches and systems based on their provided functions for data lakes, which makes this survey a useful technical reference for designing, implementing and deploying data lakes. We hope that the thorough comparison of existing solutions and the discussion of open research challenges in this survey will motivate the future development of data lake research and practice.},
  file = {/Users/dkapitan/Zotero/storage/R87AQA44/Hai et al. - 2023 - Data Lakes A Survey of Functions and Systems.pdf}
}

@article{halevymanaging,
  title = {Managing {{Google}}'s Data Lake: An Overview of the {{GOODS}} System},
  author = {Halevy, Alon and Korn, Flip and Noy, Natalya F and Olston, Christopher and Polyzotis, Neoklis and Roy, Sudip and Whang, Steven Euijong},
  abstract = {For most large enterprises today, data constitutes their core asset, along with code and infrastructure. For most enterprises, the amount of data that they produce internally has exploded in recent years. At the same time, in many cases, engineers and data scientists do not use centralized data-management systems and end up creating what became known as a data lake---a collection of datasets that often are not well organized or not organized at all and where one needs to ``fish'' for useful datasets. In this paper, we describe our experience building and deploying GOODS, a system to manage Google's internal data lake. GOODS crawls Google's infrastructure and builds a catalog of discovered datasets, including structured files, databases, spreadsheets, and even services that provide access to the data. GOODS extracts metadata about datasets in a post-hoc way: engineers continue to generate and organize datasets in the same way that they have before, and GOODS provides value without disrupting teams' practices. The technical challenges that we had to address resulted both from the scale and heterogeneity of Google's data lake and from our decision to extract metadata in a post-hoc manner. We believe that many of the lessons that we learned are applicable to building large-scale enterprise-level data-management systems in general.},
  langid = {english},
  file = {/Users/dkapitan/Zotero/storage/VNIRT3BT/Halevy et al. - Managing Google’s data lake an overview of the GO.pdf}
}

@inproceedings{harby2022data,
  title = {From {{Data Warehouse}} to {{Lakehouse}}: {{A Comparative Review}}},
  shorttitle = {From {{Data Warehouse}} to {{Lakehouse}}},
  booktitle = {2022 {{IEEE International Conference}} on {{Big Data}} ({{Big Data}})},
  author = {Harby, Ahmed A. and Zulkernine, Farhana},
  year = {2022},
  month = dec,
  pages = {389--395},
  publisher = {IEEE},
  address = {Osaka, Japan},
  doi = {10.1109/BigData55660.2022.10020719},
  urldate = {2023-04-23},
  abstract = {Digital information systems currently generate a vast amount of data every minute which emphasizes the continuing need to advance big data management systems with efficient data ingestion and knowledge extraction capabilities. To address the `big data' problems due to high volume, velocity, variety, and veracity, data management systems evolved from structured databases to big data storage systems, graph databases, data warehouses, and data lakes but each solution has its strengths and shortcomings. The need to produce actionable knowledge fast from unstructured data ingested from distributed sources requires a marriage of data warehouses and data lakes to create a data Lakehouse (LH). The objective is to use the strengths of the data warehouse in producing insights fast from processed merged data, and of the data lake in ingesting and storing high-speed unstructured data with post-storage transformation and analytics capabilities. In this paper, we present a comparative review of the existing data warehouse and data lake technology to highlight their strengths and weaknesses and propose the desired and necessary features of the LH architecture, which has recently gained a lot of attention in the big data management research community.},
  isbn = {978-1-66548-045-1},
  langid = {english},
  file = {/Users/dkapitan/Zotero/storage/H7SQYVUI/Harby and Zulkernine - 2022 - From Data Warehouse to Lakehouse A Comparative Re.pdf}
}

@misc{harby2024data,
  type = {{{SSRN Scholarly Paper}}},
  title = {Data {{Lakehouse}}: {{A Survey}} and {{Experimental Study}}},
  shorttitle = {Data {{Lakehouse}}},
  author = {Harby, Ahmed A. and Zulkernine, Farhana},
  year = {2024},
  month = mar,
  number = {4765588},
  address = {Rochester, NY},
  doi = {10.2139/ssrn.4765588},
  urldate = {2024-03-27},
  abstract = {Efficient big data management is a dire necessity to manage the exponential growth in data generated by digital information systems to produce usable knowledge. Structured databases, data lakes, and warehouses have each provided a solution with varying degrees of success. However, a new and superior solution, the data Lakehouse, has emerged to extract actionable insights from unstructured data ingested from distributed sources. By combining the strengths of data warehouses and data lakes, the data Lakehouse can process and merge data quickly while ingesting and storing high-speed unstructured data with post-storage transformation and analytics capabilities. The Lakehouse architecture offers the necessary features for optimal functionality and has gained significant attention in the big data management research community. In this paper, we compare data lake, warehouse, and lakehouse systems, highlight their strengths and shortcomings, identify the desired features to handle the evolving challenges in big data management and analysis and propose an advanced data Lakehouse architecture. We also demonstrate the performance of three state-of-the-art data management systems namely HDFS data lake, Hive data warehouse, and Delta lakehouse in managing data for analytical query responses through an experimental study.},
  langid = {english},
  keywords = {Big data,Data Lake,Data Lakehouse,Data Warehouse},
  file = {/Users/dkapitan/Zotero/storage/3THYQL7N/Harby and Zulkernine - 2024 - Data Lakehouse A Survey and Experimental Study.pdf}
}

@article{haverinen2022national,
  title = {National {{Development}} and {{Regional Differences}} in {{eHealth Maturity}} in {{Finnish Public Health Care}}: {{Survey Study}}},
  shorttitle = {National {{Development}} and {{Regional Differences}} in {{eHealth Maturity}} in {{Finnish Public Health Care}}},
  author = {Haverinen, Jari and Ker{\"a}nen, Niina and Tuovinen, Timo and Ruotanen, Ronja and Reponen, Jarmo},
  year = {2022},
  month = aug,
  journal = {JMIR Medical Informatics},
  volume = {10},
  number = {8},
  pages = {e35612},
  publisher = {JMIR Publications Inc., Toronto, Canada},
  doi = {10.2196/35612},
  urldate = {2024-03-22},
  abstract = {Background: eHealth increasingly affects the delivery of health care around the world and the quest for more efficient health systems. In Finland, the development of eHealth maturity has been systematically studied since 2003, through surveys conducted every 3 years. It has also been monitored in several international studies. The indicators used in these studies examined the availability of the electronic patient record, picture archiving and communication system, health information exchange, and other key eHealth functionalities. Objective: The first aim is to study the national development in the maturity level of eHealth in primary health care and specialized care between 2011 and 2020 in Finland. The second aim is to clarify the regional differences in the maturity level of eHealth among Finnish hospital districts in 2020. Methods: Data for this study were collected in 2011, 2014, 2017, and 2020, using web-based questionnaires from the Use of information and communication technology surveys in Finnish health care project. In total, 16 indicators were selected to describe the status of eHealth, and they were based on international eHealth studies and Finnish eHealth surveys in 3 areas: applications, regional integration, and data security and information and communications technology skills. The indicators remain the same in all the study years; therefore, the results are comparable. Results: All the specialized care organizations (21/21, 100\%) in 2011, 2014, 2017, and 2020 participated in the study. The response rate among primary health care organizations was 86.3\% (139/161) in 2011, 88.2\% (135/153) in 2014, 85.8\% (121/141) in 2017, and 95.6\% (130/136) in 2020. At the national level, the biggest developments in eHealth maturity occurred between 2011 and 2014. The development has since continued, and some indicators have been saturated. Primary health care lags behind specialized care organizations, as measured by all the indicators and throughout the period under review. Regionally, there are differences among different types of organizations. Conclusions: eHealth maturity has steadily progressed in Finland nationally, and its implementation has also been promoted through various national strategies and legislative changes. Some eHealth indicators have already been saturated and achieved an intensity of use rate of 100\%. However, the scope for development remains, especially in primary health care. As Finland has long been a pioneer in the digitalization of health care, the results of this study show that the functionalities of eHealth will be adopted in stages, and deployment will take time; therefore, national eHealth strategies and legislative changes need to be implemented in a timely manner. The comprehensive sample size used in this study allows a regional comparison in the country, compared with previous country-specific international studies.},
  copyright = {This is an open-access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work, first published JMIR Medical Informatics, is properly cited. The complete bibliographic information, a link to the original publication on https://medinform.jmir.org/, as well as this copyright and license information must be included.},
  langid = {english},
  file = {/Users/dkapitan/Zotero/storage/3PESH3Y4/Haverinen et al. - 2022 - National Development and Regional Differences in e.pdf;/Users/dkapitan/Zotero/storage/JBVDGTCZ/e35612.html}
}

@article{hcx,
  title = {{{HCX SWITCH TERMS AND CONDITIONS}}},
  langid = {english},
  file = {/Users/dkapitan/Zotero/storage/BFN9BQHM/HCX SWITCH TERMS AND CONDITIONS.pdf}
}

@article{hein2020digital,
  title = {Digital Platform Ecosystems},
  author = {Hein, Andreas and Schreieck, Maximilian and Riasanow, Tobias and Setzke, David Soto and Wiesche, Manuel and B{\"o}hm, Markus and Krcmar, Helmut},
  year = {2020},
  month = mar,
  journal = {Electronic Markets},
  volume = {30},
  number = {1},
  pages = {87--98},
  issn = {1422-8890},
  doi = {10.1007/s12525-019-00377-4},
  urldate = {2024-08-12},
  abstract = {Digital platforms are an omnipresent phenomenon that challenges incumbents by changing how we consume and provide digital products and services. Whereas traditional firms create value within the boundaries of a company or a supply chain, digital platforms utilize an ecosystem of autonomous agents to co-create value. Scholars from various disciplines, such as economics, technology management, and information systems have taken different perspectives on~digital platform ecosystems. In this Fundamentals article, we first synthesize research on digital platforms and digital platform ecosystems to provide a definition that integrates both concepts. Second, we use this definition to explain how different digital platform ecosystems vary according to three core building blocks: (1) platform ownership, (2) value-creating mechanisms, and (3) complementor autonomy. We conclude by giving an outlook on four overarching research areas that connect the building blocks: (1) technical properties and value creation; (2) complementor interaction with the ecosystem; (3) value capture; and (4) the make-or-join decision in digital platform ecosystems.},
  langid = {english},
  keywords = {D15,D4,Digital platform,Governance,O3,Openness,Ownership,Platform ecosystems},
  file = {/Users/dkapitan/Zotero/storage/8PYZ55YT/Hein et al. - 2020 - Digital platform ecosystems.pdf}
}

@article{henderson1990architectural,
  title = {Architectural {{Innovation}}: {{The Reconfiguration}} of {{Existing Product Technologies}} and the {{Failure}} of {{Established Firms}}},
  shorttitle = {Architectural {{Innovation}}},
  author = {Henderson, Rebecca and Clark, Kim},
  year = {1990},
  month = mar,
  journal = {Administrative science quarterly},
  volume = {35},
  doi = {10.2307/2393549},
  abstract = {This paper demonstrates that the traditional categorization of innovation as either incremental or radical is incomplete and potentially misleading and does not account for the sometimes disastrous effects on industry incumbents of seemingly minor improvements in technological products. We examine such innovations more closely and, distinguishing between the components of a product and the ways they are integrated into the system that is the product "architecture," define them as innovations that change the architecture of a product without changing its components. We show that architectural innovations destroy the usefulness of the architectural knowledge of established firms, and that since architectural knowledge tends to become embedded in the structure and information-processing procedures of established organizations, this destruction is difficult for firms to recognize and hard to correct. Architectural innovation therefore presents established organizations with subtle challenges that may have significant competitive implications. We illustrate the concept's explanatory force through an empirical study of the semiconductor photolithographic alignment equipment industry, which has experienced a number of architectural innovations.},
  file = {/Users/dkapitan/Zotero/storage/QLM2SY2D/Henderson and Clark - 1990 - Architectural Innovation The Reconfiguration of E.pdf}
}

@article{hermes2020digital,
  title = {The Digital Transformation of the Healthcare Industry: Exploring the Rise of Emerging Platform Ecosystems and Their Influence on the Role of Patients},
  shorttitle = {The Digital Transformation of the Healthcare Industry},
  author = {Hermes, Sebastian and Riasanow, Tobias and Clemons, Eric K. and B{\"o}hm, Markus and Krcmar, Helmut},
  year = {2020},
  month = nov,
  journal = {Business Research},
  volume = {13},
  number = {3},
  pages = {1033--1069},
  issn = {2198-2627},
  doi = {10.1007/s40685-020-00125-x},
  urldate = {2024-08-13},
  abstract = {While traditional organizations create value within the boundaries of their firm or supply chain, digital platforms leverage and orchestrate a platform-mediated ecosystem to create and co-create value with a much wider array of partners and actors. Although the change to two-sided markets and their generalization to platform ecosystems have been adopted among various industries, both academic research and industry adoption have lagged behind in the healthcare industry. To the best of our knowledge current Information Systems research has not yet incorporated an interorganizational perspective of the digital transformation of healthcare. This neglects a wide range of emerging changes, including changing segmentation of industry market participants, changing patient segments, changing patient roles as decision makers, and their interaction in patient care. This study therefore investigates the digital transformation of the healthcare industry by analyzing 1830 healthcare organizations found on Crunchbase. We derived a generic value ecosystem of the digital healthcare industry and validated our findings with industry experts from the traditional and the start-up healthcare domains. The results indicate 8 new roles within healthcare, namely: information platforms, data collection technology, market intermediaries, services for remote and on-demand healthcare, augmented and virtual reality provider, blockchain-based PHR, cloud service provider, and intelligent data analysis for healthcare provider. Our results further illustrate how these roles transform value proposition, value capture, and value delivery in the healthcare industry. We discuss competition between new entrants and incumbents and elaborate how digital health innovations contribute to the changing role of patients.},
  langid = {english},
  keywords = {Digital health,Digital transformation,Ecosystem analysis,Health information technology,Healthcare,Platform ecosystem},
  file = {/Users/dkapitan/Zotero/storage/W45D48CN/Hermes et al. - 2020 - The digital transformation of the healthcare indus.pdf}
}

@article{hersh2015outcomes,
  title = {Outcomes {{From Health Information Exchange}}: {{Systematic Review}} and {{Future Research Needs}}},
  shorttitle = {Outcomes {{From Health Information Exchange}}},
  author = {Hersh, William R. and Totten, Annette M. and Eden, Karen B. and Devine, Beth and Gorman, Paul and Kassakian, Steven Z. and Woods, Susan S. and Daeges, Monica and Pappas, Miranda and McDonagh, Marian S.},
  year = {2015},
  month = dec,
  journal = {JMIR Medical Informatics},
  volume = {3},
  number = {4},
  pages = {e5215},
  publisher = {JMIR Publications Inc., Toronto, Canada},
  doi = {10.2196/medinform.5215},
  urldate = {2024-03-22},
  abstract = {Background: Health information exchange (HIE), the electronic sharing of clinical information across the boundaries of health care organizations, has been promoted to improve the efficiency, cost-effectiveness, quality, and safety of health care delivery. Objective: To systematically review the available research on HIE outcomes and analyze future research needs. Methods: Data sources included citations from selected databases from January 1990 to February 2015. We included English-language studies of HIE in clinical or public health settings in any country. Data were extracted using dual review with adjudication of disagreements. Results: We identified 34 studies on outcomes of HIE. No studies reported on clinical outcomes (eg, mortality and morbidity) or identified harms. Low-quality evidence generally finds that HIE reduces duplicative laboratory and radiology testing, emergency department costs, hospital admissions (less so for readmissions), and improves public health reporting, ambulatory quality of care, and disability claims processing. Most clinicians attributed positive changes in care coordination, communication, and knowledge about patients to HIE. Conclusions: Although the evidence supports benefits of HIE in reducing the use of specific resources and improving the quality of care, the full impact of HIE on clinical outcomes and potential harms are inadequately studied. Future studies must address comprehensive questions, use more rigorous designs, and employ a standard for describing types of HIE. Trial Registration: PROSPERO Registry No CRD42014013285; http://www.crd.york.ac.uk/PROSPERO/ display\_record.asp?ID=CRD42014013285 (Archived by WebCite at http://www.webcitation.org/6dZhqDM8t).},
  copyright = {This is an open-access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work, first published JMIR Medical Informatics, is properly cited. The complete bibliographic information, a link to the original publication on https://medinform.jmir.org/, as well as this copyright and license information must be included.},
  langid = {english},
  file = {/Users/dkapitan/Zotero/storage/ZC77YRCV/Hersh et al. - 2015 - Outcomes From Health Information Exchange Systema.pdf;/Users/dkapitan/Zotero/storage/74F7DIGC/e39.html}
}

@misc{hl72020fhirpath,
  title = {{{FHIRPath}} ({{Normative Release}})},
  author = {{HL7}},
  year = {2020},
  month = jan,
  urldate = {2024-01-18},
  file = {/Users/dkapitan/Zotero/storage/GTGRMLZH/fhirpath.html}
}

@article{hocukeconomies,
  title = {Economies of Scope in the Aggregation of Health-Related Data},
  author = {H{\"o}c{\"u}k, Seyit and Kumar, Pradeep and Mulder, Joris and Pr{\"u}fer, Patricia and Martens, Bertin},
  langid = {english},
  file = {/Users/dkapitan/Zotero/storage/AL463C9N/Höcük et al. - Economies of scope in the aggregation of health-re.pdf}
}

@article{hoepman2023opinions,
  title = {Opinions {$\bullet$} {{Privacy Is Hard}} and {{Seven Other Myths}}},
  author = {Hoepman, Jaap-Henk},
  year = {2023},
  journal = {European Data Protection Law Review},
  volume = {9},
  number = {2},
  pages = {104--111},
  publisher = {Lexxion Publisher},
  issn = {2364284X},
  doi = {10.21552/edpl/2023/2/5},
  urldate = {2024-05-17},
  langid = {english},
  file = {/Users/dkapitan/Zotero/storage/RYJBU7SG/Hoepman - 2023 - Opinions ∙ Privacy Is Hard and Seven Other Myths.pdf}
}

@article{holmgren2023health,
  title = {Health {{Information Exchange}}: {{Understanding}} the {{Policy Landscape}} and {{Future}} of {{Data Interoperability}}},
  shorttitle = {Health {{Information Exchange}}},
  author = {Holmgren, A Jay and Esdar, Moritz and H{\"u}sers, Jens and {Coutinho-Almeida}, Jo{\~a}o},
  year = {2023},
  month = jul,
  journal = {Yearbook of Medical Informatics},
  volume = {32},
  number = {1},
  pages = {184--194},
  issn = {0943-4747},
  doi = {10.1055/s-0043-1768719},
  urldate = {2024-08-20},
  abstract = {Objectives : To review recent literature on health information exchange (HIE), focusing on the policy approach of five case study nations: the United States of America, the United Kingdom, Germany, Israel, and Portugal, as well as synthesize lessons learned across countries and provide recommendations for future research. , Methods : A narrative review of each nation's HIE policy frameworks, current state, and future HIE strategy. , Results : Key themes that emerged include the importance of both central decision-making as well as local innovation, the multiple and complex challenges of broad HIE adoption, and the varying role of HIE across different national health system structures. , Conclusion : HIE is an increasingly important capability and policy priority as electronic health record (EHR) adoption becomes more common and care delivery is increasingly digitized. While all five case study nations have adopted some level of HIE, there are significant differences across their level of data sharing infrastructure and maturity, and each nation took a different policy approach. While identifying generalizable strategies across disparate international systems is challenging, there are several common themes across successful HIE policy frameworks, such as the importance of central government prioritization of data sharing. Finally, we make several recommendations for future research to expand the breadth and depth of the literature on HIE and guide future decision-making by policymakers and practitioners.},
  pmcid = {PMC10751121},
  pmid = {37414031},
  file = {/Users/dkapitan/Zotero/storage/AB88CDYP/Holmgren et al. - 2023 - Health Information Exchange Understanding the Policy Landscape and Future of Data Interoperability.pdf}
}

@misc{home,
  title = {Home - {{FHIR Implementation Guide}} for {{ABDM}} v6.0.0},
  urldate = {2024-03-07},
  howpublished = {https://nrces.in/ndhm/fhir/r4/index.html}
}

@misc{hoseini2023semantic,
  title = {Semantic {{Data Management}} in {{Data Lakes}}},
  author = {Hoseini, Sayed and {Theissen-Lipp}, Johannes and Quix, Christoph},
  year = {2023},
  month = oct,
  number = {arXiv:2310.15373},
  eprint = {2310.15373},
  primaryclass = {cs},
  publisher = {arXiv},
  urldate = {2024-03-27},
  abstract = {In recent years, data lakes emerged as away to manage large amounts of heterogeneous data for modern data analytics. One way to prevent data lakes from turning into inoperable data swamps is semantic data management. Some approaches propose the linkage of metadata to knowledge graphs based on the Linked Data principles to provide more meaning and semantics to the data in the lake. Such a semantic layer may be utilized not only for data management but also to tackle the problem of data integration from heterogeneous sources, in order to make data access more expressive and interoperable. In this survey, we review recent approaches with a specific focus on the application within data lake systems and scalability to Big Data. We classify the approaches into (i) basic semantic data management, (ii) semantic modeling approaches for enriching metadata in data lakes, and (iii) methods for ontologybased data access. In each category, we cover the main techniques and their background, and compare latest research. Finally, we point out challenges for future work in this research area, which needs a closer integration of Big Data and Semantic Web technologies.},
  archiveprefix = {arXiv},
  keywords = {Computer Science - Artificial Intelligence,Computer Science - Computation and Language,Computer Science - Databases,Computer Science - Human-Computer Interaction},
  file = {/Users/dkapitan/Zotero/storage/WGC4V47V/Hoseini et al. - 2023 - Semantic Data Management in Data Lakes.pdf;/Users/dkapitan/Zotero/storage/XRQ7JIVP/2310.html}
}

@article{huisman2022digital,
  title = {A Digital Mobile Health Platform Increasing Efficiency and Transparency towards Universal Health Coverage in Low- and Middle-Income Countries},
  author = {Huisman, Liesbeth and {van Duijn}, Shannen Mc and Silva, Nuno and {van Doeveren}, Rianne and Michuki, Jacinta and Kuria, Moses and Otieno Okeyo, David and Okoth, Isaiah and Houben, Nathalie and {Rinke de Wit}, Tobias F. and Rogo, Khama},
  year = {2022},
  journal = {Digital Health},
  volume = {8},
  pages = {20552076221092213},
  issn = {2055-2076},
  doi = {10.1177/20552076221092213},
  abstract = {In low-and middle-income countries, achieving universal health coverage remains challenging due to insufficient, temporary and fragmented funding as well as limited accessibility to quality healthcare. Leveraging a mobile health platform can be a powerful tool to address these problems. This paper demonstrates how analysing data collected from a mobile health platform helps optimize healthcare provider networks, monitor patient flows and assess the quality and equitability of access to care. The COVID-19 pandemic reinforces the importance of real-time data on health-seeking behaviour. Between 2018 and 2019, as a Kenyan universal health coverage pilot was being planned, Kisumu County, with support from PharmAccess Foundation, implemented household-level digital registration for healthcare and collected socio-economic and healthcare claims data using the M-TIBA platform. In total, 273,350 Kisumu households enrolled. The claims data showed many patients visit higher-level facilities for ailments, that can be treated at primary care levels, unnecessarily. High-level estimate of the disease burden at participating facilities revealed rampant overprescription of pertinent medicines for highly prevalent malaria and respiratory tract infections, exemplifying clinical management deficiencies. M-TIBA data allowed tracking of individual patient trajectories. Analyses of data are shown at the aggregate level. The paper shows how mobile health platforms can be used to generate valuable insights into access to and quality of care. Funding for healthcare can be united through mobile health platforms, limiting the fragmentation in funding. They can be useful for funders, health managers and policymakers to improve the implementation of universal health coverage programs in low-and middle-income countries.},
  langid = {english},
  pmcid = {PMC9005819},
  pmid = {35433018},
  keywords = {Kenya,malaria,mobile digital health,respiratory tract infections,universal health coverage},
  file = {/Users/dkapitan/Zotero/storage/M6UV4HG6/Huisman et al. - 2022 - A digital mobile health platform increasing effici.pdf}
}

@article{hwang2024analysis,
  title = {Analysis of {{Federated Learning Paradigm}} in {{Medical Domain}}: {{Taking COVID-19}} as an {{Application Use Case}}},
  shorttitle = {Analysis of {{Federated Learning Paradigm}} in {{Medical Domain}}},
  author = {Hwang, Seong Oun and Majeed, Abdul},
  year = {2024},
  month = jan,
  journal = {Applied Sciences},
  volume = {14},
  number = {10},
  pages = {4100},
  publisher = {Multidisciplinary Digital Publishing Institute},
  issn = {2076-3417},
  doi = {10.3390/app14104100},
  urldate = {2024-05-27},
  abstract = {Federated learning (FL) has emerged as one of the de-facto privacy-preserving paradigms that can effectively work with decentralized data sources (e.g., hospitals) without acquiring any private data. Recently, applications of FL have vastly expanded into multiple domains, particularly the medical domain, and FL is becoming one of the mainstream technologies of the near future. In this study, we provide insights into FL fundamental concepts (e.g., the difference from centralized learning, functions of clients and servers, workflows, and nature of data), architecture and applications in the general medical domain, synergies with emerging technologies, key challenges (medical domain), and potential research prospects. We discuss major taxonomies of the FL systems and enlist technical factors in the FL ecosystem that are the foundation of many adversarial attacks on these systems. We also highlight the promising applications of FL in the medical domain by taking the recent COVID-19 pandemic as an application use case. We highlight potential research and development trajectories to further enhance the persuasiveness of this emerging paradigm from the technical point of view. We aim to concisely present the progress of FL up to the present in the medical domain including COVID-19 and to suggest future research trajectories in this area.},
  copyright = {http://creativecommons.org/licenses/by/3.0/},
  langid = {english},
  keywords = {adversarial attacks,AI models,COVID-19,data sharing,data sources,federated learning,medical domain,privacy preservation,privacy-preserving paradigms,private data,training data},
  file = {/Users/dkapitan/Zotero/storage/NDQC67M8/Hwang and Majeed - 2024 - Analysis of Federated Learning Paradigm in Medical.pdf}
}

@misc{ibisproject,
  title = {Ibis-Project/Ibis},
  year = {2024},
  month = may,
  urldate = {2024-05-27},
  abstract = {the portable Python dataframe library},
  copyright = {Apache-2.0},
  howpublished = {Ibis Project},
  keywords = {bigquery,clickhouse,dask,database,datafusion,duckdb,impala,mssql,mysql,pandas,polars,postgresql,pyarrow,pyspark,python,snowflake,sql,sqlalchemy,sqlite,trino}
}

@misc{ihe,
  title = {{{IHE Publications}}},
  urldate = {2024-08-20},
  howpublished = {https://profiles.ihe.net/index.html}
}

@misc{InstantOpenHIEv2,
  title = {Instant {{OpenHIE}} v2.2.0},
  year = {2024},
  month = jan,
  urldate = {2024-02-05},
  abstract = {Instantly deploy complex HIE components},
  howpublished = {https://jembi.gitbook.io/instant-v2/},
  langid = {english},
  file = {/Users/dkapitan/Zotero/storage/UUQGLGD7/instant-v2.html}
}

@misc{interoperability,
  title = {Interoperability {{Layer}} - {{Use Cases}} and {{Requirements}} - {{Communities}} \& {{Projects}} - {{OpenHIE Wiki}}},
  urldate = {2024-05-27},
  howpublished = {https://wiki.ohie.org/display/CP/Interoperability+Layer+-+Use+Cases+and+Requirements}
}

@misc{islam2023fhir,
  title = {Fhir.Resources: {{FHIR Resources}} as {{Model Class}}},
  shorttitle = {Fhir.Resources},
  author = {Islam, Md Nazrul},
  year = {2023},
  month = dec,
  urldate = {2023-01-22},
  copyright = {BSD License},
  keywords = {fhir,health IT,healthcare,hl7,python,resources},
  file = {/Users/dkapitan/Zotero/storage/DQIT824C/fhir.resources.html}
}

@article{izudi2023experiences,
  title = {Experiences of Mothers and Health Workers with {{MomCare}} and {{SafeCare}} Bundles in {{Kenya}} and {{Tanzania}}: {{A}} Qualitative Evaluation},
  shorttitle = {Experiences of Mothers and Health Workers with {{MomCare}} and {{SafeCare}} Bundles in {{Kenya}} and {{Tanzania}}},
  author = {Izudi, Jonathan and Owoko, Henry Odero and Bagayoko, Moussa and Kadengye, Damazo},
  year = {2023},
  journal = {PloS One},
  volume = {18},
  number = {11},
  pages = {e0294536},
  issn = {1932-6203},
  doi = {10.1371/journal.pone.0294536},
  abstract = {Between 2019 and 2022, the digital dividend project (DDP), a technology-based intervention that combined care (MomCare) and quality improvement (SafeCare) bundles to empower mothers to access quality care during pregnancy, labor, and delivery, and postnatally, was implemented in Kenya and Tanzania aiming to improve maternal and newborn health outcomes. We describe the experiences of the mothers in accessing and utilizing health services under the bundles, and the experiences of the health workers in providing the services. Between November and December 2022, we conducted a qualitative evaluation across health facilities in Kenya and Tanzania. We held Interviews with mothers (pregnant and postpartum women who had benefited from the care bundles) and health workers (physicians, nurses, and midwives who provided the care bundles, including health facility In-Charges) at the antenatal care (ANC), skilled birth attendance (SBA), and postnatal care (PNC) service delivery points. We performed content analysis. Findings are reported using themes and quotes from the participants. We included 127 mothers (Kenya = 76, Tanzania = 51) and 119 health workers. Findings revealed that among mothers, the care bundles eased access to health services, ensured easy access and optimal ANC use, provision of respectful care, removed financial constraints, and led to the receipt of sufficient health education. Health workers reported that the care bundles offered them a new opportunity to provide quality maternal and newborn care and to adhere to the standard of care besides experiencing a positive and fulfilling practice. Health systems improvements included prompt emergency response and continual care, infrastructural developments, medical supplies and logistics, staffing, and increased documentation. Overall, the care bundles led to the strengthening of the healthcare system (staffing, service delivery, financing, supplies/logistics, and information management) in order to deliver quality maternal and child health services. The bundles should be replicated in settings with similar maternal and child health challenges.},
  langid = {english},
  pmcid = {PMC10653531},
  pmid = {37972017},
  keywords = {Antenatal care,Child,Child health,Female,Health care facilities,Health education and awareness,Health systems strengthening,Humans,Infant Newborn,Kenya,Labor and delivery,Maternal Health Services,Midwifery,Mothers,Postnatal care,Pregnancy,Prenatal Care,Tanzania},
  file = {/Users/dkapitan/Zotero/storage/N6EPE4YD/Izudi et al. - 2023 - Experiences of mothers and health workers with Mom.pdf}
}

@article{jain2023analyzing,
  title = {Analyzing and {{Comparing Lakehouse Storage Systems}}},
  author = {Jain, Paras and Kraft, Peter and Power, Conor and Das, Tathagata and Stoica, Ion and Zaharia, Matei},
  year = {2023},
  abstract = {Lakehouse storage systems that implement ACID transactions and other management features over data lake storage, such as Delta Lake, Apache Hudi and Apache Iceberg, have rapidly grown in popularity, replacing traditional data lakes at many organizations. These open storage systems with rich management features promise to simplify management of large datasets, accelerate SQL workloads, and offer fast, direct file access for other workloads, such as machine learning. However, the research community has not explored the tradeoffs in designing lakehouse systems in detail. In this paper, we analyze the designs of the three most popular lakehouse storage systems---Delta Lake, Hudi and Iceberg---and compare their performance and features among varying axes based on these designs. We also release a simple benchmark, LHBench, that researchers can use to compare other designs. LHBench is available at https://github.com/lhbench/lhbench.},
  langid = {english},
  file = {/Users/dkapitan/Zotero/storage/AQ2TN7SR/p92-jain.pdf;/Users/dkapitan/Zotero/storage/KLZG5RE5/Jain et al. - 2023 - Analyzing and Comparing Lakehouse Storage Systems.pdf}
}

@article{janssen2024taxonomy,
  title = {A {{Taxonomy}} for {{Health Information Systems}}},
  author = {Janssen, Anna and Donnelly, Candice and Shaw, Tim},
  year = {2024},
  month = may,
  journal = {Journal of Medical Internet Research},
  volume = {26},
  pages = {e47682},
  issn = {1438-8871},
  doi = {10.2196/47682},
  urldate = {2024-08-16},
  abstract = {The health sector is highly digitized, which is enabling the collection of vast quantities of electronic data about health and well-being. These data are collected by a diverse array of information and communication technologies, including systems used by health care organizations, consumer and community sources such as information collected on the web, and passively collected data from technologies such as wearables and devices. Understanding the breadth of IT that collect these data and how it can be actioned is a challenge for the significant portion of the digital health workforce that interact with health data as part of their duties but are not for informatics experts. This viewpoint aims to present a taxonomy categorizing common information and communication technologies that collect electronic data. An initial classification of key information systems collecting electronic health data was undertaken via a rapid review of the literature. Subsequently, a purposeful search of the scholarly and gray literature was undertaken to extract key information about the systems within each category to generate definitions of the systems and describe the strengths and limitations of these systems.},
  langid = {english},
  file = {/Users/dkapitan/Zotero/storage/2EDC4W8C/Janssen et al. - 2024 - A Taxonomy for Health Information Systems.pdf}
}

@article{janssen2024taxonomya,
  title = {A {{Taxonomy}} for {{Health Information Systems}}},
  author = {Janssen, Anna and Donnelly, Candice and Shaw, Tim},
  year = {2024},
  month = may,
  journal = {Journal of Medical Internet Research},
  volume = {26},
  number = {1},
  pages = {e47682},
  publisher = {JMIR Publications Inc., Toronto, Canada},
  doi = {10.2196/47682},
  urldate = {2024-08-26},
  abstract = {The health sector is highly digitized, which is enabling the collection of vast quantities of electronic data about health and well-being. These data are collected by a diverse array of information and communication technologies, including systems used by health care organizations, consumer and community sources such as information collected on the web, and passively collected data from technologies such as wearables and devices. Understanding the breadth of IT that collect these data and how it can be actioned is a challenge for the significant portion of the digital health workforce that interact with health data as part of their duties but are not for informatics experts. This viewpoint aims to present a taxonomy categorizing common information and communication technologies that collect electronic data. An initial classification of key information systems collecting electronic health data was undertaken via a rapid review of the literature. Subsequently, a purposeful search of the scholarly and gray literature was undertaken to extract key information about the systems within each category to generate definitions of the systems and describe the strengths and limitations of these systems.},
  langid = {english},
  file = {/Users/dkapitan/Zotero/storage/PE5MT8L7/e47682.html}
}

@article{jindal2021magpie,
  title = {Magpie: {{Python}} at {{Speed}} and {{Scale}} Using {{Cloud Backends}}},
  author = {Jindal, Alekh and Emani, K Venkatesh and Daum, Maureen and Poppe, Olga and Haynes, Brandon and Pavlenko, Anna and Gupta, Ayushi and Ramachandra, Karthik and Curino, Carlo and Mueller, Andreas and Wu, Wentao and Patel, Hiren},
  year = {2021},
  abstract = {Python has become overwhelmingly popular for ad-hoc data analysis, and Pandas dataframes have quickly become the de facto standard API for data science. However, performance and scaling to large datasets remain significant challenges. This is in stark contrast with the world of databases, where decades of investments have led to both sub-millisecond latencies for small queries and many orders of magnitude better scalability for large analytical queries. Furthermore, databases offer enterprise-grade features (e.g., transactions, fine-grained access control, tamper-proof logging, encryption) as well as a mature ecosystem of tools in modern clouds.},
  langid = {english},
  file = {/Users/dkapitan/Zotero/storage/7KTYJ53C/Jindal et al. - 2021 - Magpie Python at Speed and Scale using Cloud Back.pdf}
}

@article{jones2021landscape,
  title = {A Landscape Survey of Planned {{SMART}}/{{HL7}} Bulk {{FHIR}} Data Access {{API}} Implementations and Tools},
  author = {Jones, James and Gottlieb, Daniel and Mandel, Joshua C and Ignatov, Vladimir and Ellis, Alyssa and Kubick, Wayne and Mandl, Kenneth D},
  year = {2021},
  month = jun,
  journal = {Journal of the American Medical Informatics Association},
  volume = {28},
  number = {6},
  pages = {1284--1287},
  issn = {1527-974X},
  doi = {10.1093/jamia/ocab028},
  urldate = {2023-01-20},
  abstract = {The Office of National Coordinator for Health Information Technology final rule implementing the interoperability and information blocking provisions of the 21st Century Cures Act requires support for two SMART (Substitutable Medical Applications, Reusable Technologies) application programming interfaces (APIs) and instantiates Health Level Seven International (HL7) Fast Healthcare Interoperability Resources (FHIR) as a lingua franca for health data. We sought to assess the current state and near-term plans for the SMART/HL7 Bulk FHIR Access API implementation across organizations including electronic health record vendors, cloud vendors, public health contractors, research institutions, payors, FHIR tooling developers, and other purveyors of health information technology platforms. We learned that many organizations not required through regulation to use standardized bulk data are rapidly implementing the API for a wide array of use cases. This may portend an unprecedented level of standardized population-level health data exchange that will support an apps and analytics ecosystem. Feedback from early adopters on the API's limitations and unsolved problems in the space of population health are highlighted.},
  file = {/Users/dkapitan/Zotero/storage/PG68K5CE/Jones et al. - 2021 - A landscape survey of planned SMARTHL7 bulk FHIR .pdf;/Users/dkapitan/Zotero/storage/3NTEYRHE/6155897.html}
}

@article{jordan2022selecting,
  title = {Selecting {{Privacy-Enhancing Technologies}} for {{Managing Health Data Use}}},
  author = {Jordan, Sara and Fontaine, Clara and {Hendricks-Sturrup}, Rachele},
  year = {2022},
  month = mar,
  journal = {Frontiers in Public Health},
  volume = {10},
  pages = {814163},
  issn = {2296-2565},
  doi = {10.3389/fpubh.2022.814163},
  urldate = {2023-02-04},
  abstract = {Privacy protection for health data is more than simply stripping datasets of specific identifiers. Privacy protection increasingly means the application of privacy-enhancing technologies (PETs), also known as privacy engineering. Demands for the application of PETs are not yet met with ease of use or even understanding. This paper provides a scope of the current peer-reviewed evidence regarding the practical use or adoption of various PETs for managing health data privacy. We describe the state of knowledge of PETS for the use and exchange of health data specifically and build a practical perspective on the steps needed to improve the standardization of the application of PETs for diverse uses of health data.},
  pmcid = {PMC8967420},
  pmid = {35372185},
  file = {/Users/dkapitan/Zotero/storage/9Z6PVM72/Jordan et al. - 2022 - Selecting Privacy-Enhancing Technologies for Manag.pdf}
}

@article{karamagi2022ehealth,
  title = {{{eHealth}} or E-{{Chaos}}: {{The}} Use of {{Digital Health Interventions}} for {{Health Systems Strengthening}} in Sub-{{Saharan Africa}} over the Last 10 Years: {{A}} Scoping Review},
  shorttitle = {{{eHealth}} or E-{{Chaos}}},
  author = {Karamagi, Humphrey C and Muneene, Derrick and Droti, Benson and Jepchumba, Violet and Okeibunor, Joseph C and Nabyonga, Juliet and Asamani, James Avoka and Traore, Moussa and Kipruto, Hillary},
  year = {2022},
  month = dec,
  journal = {Journal of Global Health},
  volume = {12},
  pages = {04090},
  issn = {2047-2978, 2047-2986},
  doi = {10.7189/jogh.12.04090},
  urldate = {2024-02-05},
  abstract = {Background Digital health solutions are a potent and complementary intervention in health system strengthening to accelerate universal access to health services. Implementing scalable, sustainable, and integrated digital solutions in a coordinated manner is necessary to experience the benefits of digital interventions in health systems. We sought to establish the breadth and scope of available digital health interventions (DHIs) and their functions in sub-Saharan Africa. Methods: We conducted a scoping review according to the Joanne Briggs Institute's reviewers manual and followed the Preferred Reporting Items for Systematic Reviews and Meta-Analyses - Extension for Scoping Reviews (PRISMA-ScR) checklist and explanation. We retrieved data from the WHO Digital Health Atlas (DHA), the WHO e-Health country profiles report of 2015, and electronic databases. The protocol has been deposited in an open-source platform -- the Open Science Framework at https://osf.io/5kzq7. Results The researchers retrieved 983 digital tools used to strengthen health systems in sub-Saharan Africa over the past 10 years. We included 738 DHIs in the analysis while 245 were excluded for not meeting the inclusion criteria. We observed a disproportionate distribution of DHIs towards service delivery (81.7\%, n\,=\,603), health care providers (91.8\%, n\,=\,678), and access and use of information (84.1\%, n\,=\,621). Fifty-three percent (53.4\%, n\,=\,394) of the solutions are established and 47.5\% (n\,=\,582) were aligned to 20\% (n\,=\,5) of the system categories. Conclusions Sub-Saharan Africa is endowed with digital health solutions in both numbers and distinct functions. It is lacking in coordination, integration, scalability, sustainability, and equitable distribution of investments in digital health. Digital health policymakers in sub-Saharan Africa need to urgently institute coordination mechanisms to terminate unending duplication and disjointed vertical implementations and manage solutions for scale. Central to this would be to build digital health leadership in countries within SSA, adopt standards and interoperability frameworks; advocate for more investments into lagging components, and promote multi-purpose solutions to halt the seeming ``e-chaos'' and progress to sustainable e-health solutions.},
  langid = {english},
  file = {/Users/dkapitan/Zotero/storage/549QGYAI/jogh-12-04090.pdf;/Users/dkapitan/Zotero/storage/U2E7IBUE/jogh-12-04090-s001.pdf}
}

@article{karume2012trends,
  title = {Trends in {{Adoption}} of {{Open Source Software}} in {{Africa}}},
  author = {Karume, Simon and Mbugua, Samuel},
  year = {2012},
  month = nov,
  journal = {Computing Trendz - The Journal of Emerging Trends in Information Technology},
  volume = {3},
  pages = {1509--1515},
  abstract = {In the context of limited financial resources and capacities, Africa can examine how to better use the opportunities presented by the emergence of free and open source software (FOSS) to leapfrog into the information age and bridge the digital divide through reduced costs and less dependency on imported technology. This paper examines the adoption trends of open source software in Africa and seeks to establish the current global placing of the continent in adoption and use of FOSS. To get a better view of the current FOSS situation in Africa, the study explores the penetration of FOSS into Africa software market and how various Governments react to the use of FOSS. Through scrutiny of literature on adoption and use of open source software in Africa as well as previous and emerging initiatives to promote the use of open source software in the region, the paper presents preliminary findings of the trends observed. Further using the data gathered the paper attempts to forecast the future of FOSS in Africa and the probable implications on the development agenda of the continent.},
  file = {/Users/dkapitan/Zotero/storage/GLLB663X/Karume and Mbugua - 2012 - Trends in Adoption of Open Source Software in Afri.pdf}
}

@article{keller2021paradox,
  title = {The {{Paradox}} of {{Open}}},
  author = {Keller, Paul and Tarkowski, Alek},
  year = {2021},
  month = mar,
  journal = {Open Future},
  publisher = {Open Future Foundation},
  urldate = {2024-03-25},
  abstract = {In today's digital environment, openness serves as both a challenge to concentrations of power and its enabler. Solving this paradox is at the heart of our work, which focuses on three objectives.},
  langid = {english},
  file = {/Users/dkapitan/Zotero/storage/GRW8I2Y9/Keller and Tarkowski - 2021 - The Paradox of Open.pdf}
}

@misc{kelley2020digital,
  title = {Digital {{Health Platform Handbook}}: {{Building}} a {{Digital Information Infrastructure}} ({{Infostructure}}) for {{Health}}},
  author = {Kelley, Edward and Zandi, Diana and Krishnamurthy, Ramesh and Mehl, Garrett and Novillo, David and Muneene, Derrick and Nour, Mohamed and Taliesin, Brian and Leitner, Carl and Althauser, Caren and Schaefer, Merrick and Ganesh, Jai and Marcelo, Alvin and Ramkumar, P S and Vota, Wayan and Kumar, Manish and Joshi, Surabhi and Shehadeh, Melissa Harper and Nueno, Violeta P{\'e}rez and Pye, Evan and Shokralla, Mariam},
  year = {2020},
  langid = {english},
  file = {/Users/dkapitan/Zotero/storage/7FD9XT6F/Kelley et al. - Digital Health Platform Handbook Building a Digital Information Infrastructure (Infostructure) for.pdf}
}

@article{khalid2021standardized,
  title = {A Standardized Analytics Pipeline for Reliable and Rapid Development and Validation of Prediction Models Using Observational Health Data},
  author = {Khalid, Sara and Yang, Cynthia and Blacketer, Clair and {Duarte-Salles}, Talita and {Fern{\'a}ndez-Bertol{\'i}n}, Sergio and Kim, Chungsoo and Park, Rae Woong and Park, Jimyung and Schuemie, Martijn J. and Sena, Anthony G. and Suchard, Marc A. and You, Seng Chan and Rijnbeek, Peter R. and Reps, Jenna M.},
  year = {2021},
  month = nov,
  journal = {Computer Methods and Programs in Biomedicine},
  volume = {211},
  pages = {106394},
  issn = {0169-2607},
  doi = {10.1016/j.cmpb.2021.106394},
  urldate = {2024-05-27},
  abstract = {Background and objective As a response to the ongoing COVID-19 pandemic, several prediction models in the existing literature were rapidly developed, with the aim of providing evidence-based guidance. However, none of these COVID-19 prediction models have been found to be reliable. Models are commonly assessed to have a risk of bias, often due to insufficient reporting, use of non-representative data, and lack of large-scale external validation. In this paper, we present the Observational Health Data Sciences and Informatics (OHDSI) analytics pipeline for patient-level prediction modeling as a standardized approach for rapid yet reliable development and validation of prediction models. We demonstrate how our analytics pipeline and open-source software tools can be used to answer important prediction questions while limiting potential causes of bias (e.g., by validating phenotypes, specifying the target population, performing large-scale external validation, and publicly providing all analytical source code). Methods We show step-by-step how to implement the analytics pipeline for the question: `In patients hospitalized with COVID-19, what is the risk of death 0 to 30 days after hospitalization?'. We develop models using six different machine learning methods in a USA claims database containing over 20,000 COVID-19 hospitalizations and externally validate the models using data containing over 45,000 COVID-19 hospitalizations from South Korea, Spain, and the USA. Results Our open-source software tools enabled us to efficiently go end-to-end from problem design to reliable Model Development and evaluation. When predicting death in patients hospitalized with COVID-19, AdaBoost, random forest, gradient boosting machine, and decision tree yielded similar or lower internal and external validation discrimination performance compared to L1-regularized logistic regression, whereas the MLP neural network consistently resulted in lower discrimination. L1-regularized logistic regression models were well calibrated. Conclusion Our results show that following the OHDSI analytics pipeline for patient-level prediction modelling can enable the rapid development towards reliable prediction models. The OHDSI software tools and pipeline are open source and available to researchers from all around the world.},
  keywords = {COVID-19,Data harmonization,Data quality control,Distributed data network,Machine learning,Risk prediction},
  file = {/Users/dkapitan/Zotero/storage/D7HZSKV3/Khalid et al. - 2021 - A standardized analytics pipeline for reliable and.pdf}
}

@article{khan2021decolonising,
  title = {Decolonising Global Health in 2021: A Roadmap to Move from Rhetoric to Reform},
  shorttitle = {Decolonising Global Health in 2021},
  author = {Khan, Mishal and Abimbola, Seye and Aloudat, Tammam and Capobianco, Emanuele and Hawkes, Sarah and {Rahman-Shepherd}, Afifah},
  year = {2021},
  month = mar,
  journal = {BMJ Global Health},
  volume = {6},
  number = {3},
  pages = {e005604},
  publisher = {BMJ Specialist Journals},
  issn = {2059-7908},
  doi = {10.1136/bmjgh-2021-005604},
  urldate = {2024-08-12},
  abstract = {Decolonising global health was a hot topic in 2020. It was the subject of more than 50 academic articles between January and December 2020, appeared as a new area covered in numerous conferences, and featured in public statements by leaders of global health organisations. Although its aims have not been formally defined, we see `decolonising global health' as a movement that fights against ingrained systems of dominance and power in the work to improve the health of populations, whether this occurs between countries, including between previously colonising and plundered nations, and within countries, for example the privileging of what Connell calls research-based knowledge formation over the lived experience of people themselves.1 2 It is well documented---although often overlooked---that global health has evolved from colonial and tropical medicine, which were `designed to control colonised populations and make political and economic exploitation by European and North American powers easier'.3 The operations of many organisations active in global health thus perpetuate the very power imbalances they claim to rectify, through colonial and extractive attitudes, and policies and practices that concentrate resources, expertise, data and branding within high-income country (HIC) institutions.4 5 As a group of global health practitioners from different backgrounds, we reflect on our personal and professional experiences of systems and processes that institutionalise power imbalances. In this article, we propose a roadmap for global health practitioners, like us, who want to see rhetoric turn into reforms, focusing on systemic changes needed in organisations led from HICs. This is important now, because the flurry of statements and virtue signalling in 2020, could, in {\dots}},
  chapter = {Editorial},
  copyright = {{\copyright} Author(s) (or their employer(s)) 2021. Re-use permitted under CC BY-NC. No commercial re-use. See rights and permissions. Published by BMJ.. http://creativecommons.org/licenses/by-nc/4.0/This is an open access article distributed in accordance with the Creative Commons Attribution Non Commercial (CC BY-NC 4.0) license, which permits others to distribute, remix, adapt, build upon this work non-commercially, and license their derivative works on different terms, provided the original work is properly cited, appropriate credit is given, any changes made indicated, and the use is non-commercial. See:~http://creativecommons.org/licenses/by-nc/4.0/.},
  langid = {english},
  pmid = {33758016},
  keywords = {health policy,health systems},
  file = {/Users/dkapitan/Zotero/storage/4DVLKGCY/Khan et al. - 2021 - Decolonising global health in 2021 a roadmap to move from rhetoric to reform.pdf}
}

@misc{khisif,
  title = {Kenya {{Health Information Systems Interoperability Framework}}},
  file = {/Users/dkapitan/Zotero/storage/RD2MGAQ6/Kenya Health Information Systems Interoperability Framework.pdf}
}

@article{kickbusch2021lancet,
  title = {The {{Lancet}} and {{Financial Times Commission}} on Governing Health Futures 2030: Growing up in a Digital World},
  shorttitle = {The {{Lancet}} and {{Financial Times Commission}} on Governing Health Futures 2030},
  author = {Kickbusch, Ilona and Piselli, Dario and Agrawal, Anurag and Balicer, Ran and Banner, Olivia and Adelhardt, Michael and Capobianco, Emanuele and Fabian, Christopher and Gill, Amandeep Singh and Lupton, Deborah and Medhora, Rohinton P. and Ndili, Njide and Ry{\'s}, Andrzej and Sambuli, Nanjira and Settle, Dykki and Swaminathan, Soumya and Morales, Jeanette Vega and Wolpert, Miranda and Wyckoff, Andrew W. and Xue, Lan and Bytyqi, Aferdita and Franz, Christian and Gray, Whitney and Holly, Louise and Neumann, Micaela and Panda, Lipsa and Smith, Robert D. and Stevens, Enow Awah Georges and Wong, Brian Li Han},
  year = {2021},
  month = nov,
  journal = {The Lancet},
  volume = {398},
  number = {10312},
  pages = {1727--1776},
  publisher = {Elsevier},
  issn = {0140-6736, 1474-547X},
  doi = {10.1016/S0140-6736(21)01824-9},
  urldate = {2023-02-16},
  langid = {english},
  pmid = {34706260},
  file = {/Users/dkapitan/Zotero/storage/CCSPHD2V/Kickbusch et al. - 2021 - The Lancet and Financial Times Commission on gover.pdf}
}

@article{kossi2013developing,
  title = {Developing Decentralised Health Information Systems in Developing Countries --Cases from {{Sierra Leone}} and {{Kenya}}},
  author = {Kossi, Edem Kwame and S{\ae}b{\o}, Johan Ivar and Braa, J{\o}rn and Jalloh, Mohamed Mumeneeh and Manya, Ayub},
  year = {2013},
  journal = {The Journal of Community Informatics},
  volume = {9},
  number = {2},
  issn = {1712-4441},
  doi = {10.15353/joci.v9i2.3164},
  urldate = {2024-08-12},
  abstract = {Health service provision is a public concern that mostly takes place at community level, through primary health care. Using cases from Sierra Leone and Kenya, this study shows how country health information systems, producing simple information products such as quarterly bulletins and league tables being distributed widely, have enabled the communities to be engaged in improving the health status of the population. The community based information systems were part of a national system and the usefulness of comparing local data with data from other communities and from across the country in pursuing equity in health services provision is demonstrated. A community based information system is thus benefiting from being part of and integrated with the larger national system. The article presents and discusses community based participatory approaches to developing information systems which are enabling the community to take ownership and `cultivate' culturally appropriate systems. Illustrated by the cases, the article argues that modern ICT and Internet based technologies, and even `cloud' based infrastructures, are indeed appropriate technologies even at community level in rural Africa.},
  copyright = {Copyright (c)},
  langid = {english},
  keywords = {Health Information Systems,Information Use,Kenya,Participatory Design,Sierra Leone},
  file = {/Users/dkapitan/Zotero/storage/ISG2JQDW/Kossi et al. - 2013 - Developing decentralised health information systems in developing countries –cases from Sierra Leone.pdf}
}

@misc{krishnamurthy2005analysis,
  type = {{{SSRN Scholarly Paper}}},
  title = {An {{Analysis}} of {{Open Source Business Models}}},
  author = {Krishnamurthy, Sandeep},
  year = {2005},
  month = jan,
  number = {650001},
  address = {Rochester, NY},
  urldate = {2024-02-29},
  abstract = {Open-source software is not for hobbyists any more.  Instead, it is a business strategy with broad applicability.  Businesses can be built around this idea.  In this paper, I want the reader to grapple with the specifics of how to build and grow such a business.  To this end, I have proposed three fundamental business models - Distributor, Software producer [GPL and non-GPL] and the Third-Party Service Provider.  These are sustainable models that can lead to robust revenue streams.  The business models provided here can be enhanced by the addition of further revenue streams.  For instance, we now know that certification of developers on an Open-Source product can lead to strong revenues.  Not all products have the same profit potential.  Therefore, not all Open Source Software products have the same profit potential.  I have classified Open Source Software products into four categories - Stars, High-profile nichers, Low-profile nichers and Mainstream utilities.  Businesses can be built around Stars.  High-profile nichers can lead to robust revenue streams if properly marketed.  The other two categories may not lead to high profits.  Since many Open Source Software products are freely available, managers must scan public repositories to find out which products will be suitable for their business.  The future of Open Source Software is bright.  Increasingly, we will find that these products will take a central role in the realm of software and will find a larger place in all our lives.},
  langid = {english},
  keywords = {Business Model,Open Source},
  file = {/Users/dkapitan/Zotero/storage/GV5RDBTM/Krishnamurthy - 2005 - An Analysis of Open Source Business Models.pdf}
}

@inproceedings{kurniawan2019midwife,
  title = {Midwife Service Coverage, Quality of Work, and Client Health Improved after Deployment of an {{OpenSRP-driven}} Client Management Application in {{Indonesia}}},
  booktitle = {5th {{International Conference}} on {{Health Sciences}} ({{ICHS}} 2018)},
  author = {Kurniawan, Kevin and FitriaSyah, Inraini and Jayakusuma, Ahmad Rafi and Armis, Resty Asmauryanah and Lubis, Yusran and Haryono, Muhammad Abdi and Harefa, Benyamin and Shankar, Anuraj},
  year = {2019},
  month = nov,
  pages = {155--162},
  publisher = {Atlantis Press},
  issn = {2468-5739},
  doi = {10.2991/ichs-18.2019.21},
  urldate = {2024-01-22},
  abstract = {The quality of maternal and child health services remains suboptimal in most low and middleincome countries (LMIC). Data are routinely collected with paper-based systems but are incomplete, underutilized, and reported as poorly-usable aggregated indicators. Therefore, we developed the Open Smart Register Platform (OpenSRP) application for midwives in...},
  isbn = {978-94-6252-824-6},
  langid = {english},
  file = {/Users/dkapitan/Zotero/storage/AV5DFWKS/Kurniawan2019midwife.pdf;/Users/dkapitan/Zotero/storage/JB3NXXH3/Kurniawan et al. - 2019 - Midwife service coverage, quality of work, and cli.pdf}
}

@article{labrique2018besta,
  title = {Best Practices in Scaling Digital Health in Low and Middle Income Countries},
  author = {Labrique, Alain B. and Wadhwani, Christina and Williams, Koku Awoonor and Lamptey, Peter and Hesp, Cees and Luk, Rowena and Aerts, Ann},
  year = {2018},
  month = nov,
  journal = {Globalization and Health},
  volume = {14},
  number = {1},
  pages = {103},
  issn = {1744-8603},
  doi = {10.1186/s12992-018-0424-z},
  urldate = {2024-08-12},
  abstract = {Healthcare challenges in low and middle income countries (LMICs) have been the focus of many digital initiatives that have aimed to improve both access to healthcare and the quality of healthcare delivery. Moving beyond the initial phase of piloting and experimentation, these initiatives are now more clearly focused on the need for effective scaling and integration to provide sustainable benefit to healthcare systems.},
  langid = {english},
  keywords = {Digital health,Health policy,Health system,Intervention,low and middle income countries,mHealth,Programme sustainability},
  file = {/Users/dkapitan/Zotero/storage/2HIHHKTW/Labrique et al. - 2018 - Best practices in scaling digital health in low and middle income countries.pdf}
}

@article{lamer2024data,
  title = {Data {{Lake}}, {{Data Warehouse}}, {{Datamart}}, and {{Feature Store}}: {{Their Contributions}} to the {{Complete Data Reuse Pipeline}}},
  shorttitle = {Data {{Lake}}, {{Data Warehouse}}, {{Datamart}}, and {{Feature Store}}},
  author = {Lamer, Antoine and {Saint-Dizier}, Chlo{\'e} and Paris, Nicolas and Chazard, Emmanuel},
  year = {2024},
  month = jul,
  journal = {JMIR Medical Informatics},
  volume = {12},
  number = {1},
  pages = {e54590},
  publisher = {JMIR Publications Inc., Toronto, Canada},
  doi = {10.2196/54590},
  urldate = {2024-08-12},
  abstract = {The growing adoption and utilization of health information technology has generated a wealth of clinical data in electronic format, offering opportunities for data reuse beyond direct patient care. However, as data are distributed across multiple software, it becomes challenging to cross-reference information between sources due to differences in formats, vocabularies, technologies, and the absence of common identifiers among software. To address these challenges, hospitals have adopted data warehouses to consolidate and standardize these data for research. Additionally, as a complement or alternative, data lakes store both source data and metadata in a detailed and unprocessed format, empowering exploration, manipulation, and adaptation of the data to meet specific analytical needs. Subsequently, datamarts are utilized to further refine data into usable information tailored to specific research questions. However, for efficient analysis, a feature store is essential to pivot and denormalize the data, simplifying queries. In conclusion, while data warehouses are crucial, data lakes, datamarts and feature stores play essential and complementary roles in facilitating data reuse for research and analysis in healthcare.},
  copyright = {This is an open-access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work, first published JMIR Medical Informatics, is properly cited. The complete bibliographic information, a link to the original publication on https://medinform.jmir.org/, as well as this copyright and license information must be included.},
  langid = {english},
  file = {/Users/dkapitan/Zotero/storage/QEDUKQIP/e54590.html}
}

@article{lee2024now,
  title = {Now {{Is}} the {{Time}} to {{Strengthen Government-Academic Data Infrastructures}} to {{Jump-Start Future Public Health Crisis Response}}},
  author = {Lee, Jian-Sin and Tyler, Allison R. B. and Veinot, Tiffany Christine and Yakel, Elizabeth},
  year = {2024},
  month = apr,
  journal = {JMIR Public Health and Surveillance},
  volume = {10},
  number = {1},
  pages = {e51880},
  publisher = {JMIR Publications Inc., Toronto, Canada},
  doi = {10.2196/51880},
  urldate = {2024-05-27},
  abstract = {During public health crises, the significance of rapid data sharing cannot be overstated. In attempts to accelerate COVID-19 pandemic responses, discussions within society and scholarly research have focused on data sharing among health care providers, across government departments at different levels, and on an international scale. A lesser-addressed yet equally important approach to sharing data during the COVID-19 pandemic and other crises involves cross-sector collaboration between government entities and academic researchers. Specifically, this refers to dedicated projects in which a government entity shares public health data with an academic research team for data analysis to receive data insights to inform policy. In this viewpoint, we identify and outline documented data sharing challenges in the context of COVID-19 and other public health crises, as well as broader crisis scenarios encompassing natural disasters and humanitarian emergencies. We then argue that government-academic data collaborations have the potential to alleviate these challenges, which should place them at the forefront of future research attention. In particular, for researchers, data collaborations with government entities should be considered part of the social infrastructure that bolsters their research efforts toward public health crisis response. Looking ahead, we propose a shift from ad hoc, intermittent collaborations to cultivating robust and enduring partnerships. Thus, we need to move beyond viewing government-academic data interactions as 1-time sharing events. Additionally, given the scarcity of scholarly exploration in this domain, we advocate for further investigation into the real-world practices and experiences related to sharing data from government sources with researchers during public health crises.},
  copyright = {Unless stated otherwise, all articles are open-access distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/2.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work ("first published in the Journal of Medical Internet Research...") is properly cited with original URL and bibliographic citation information. The complete bibliographic information, a link to the original publication on http://www.jmir.org/, as well as this copyright and license information must be included.},
  langid = {english},
  file = {/Users/dkapitan/Zotero/storage/GT8M6PM4/Lee et al. - 2024 - Now Is the Time to Strengthen Government-Academic .pdf}
}

@article{lee2024standard,
  title = {Behind and beyond the Standard(Ization) Trap: Diversifying Power Sources by Differentiating Centralization and Standardization},
  shorttitle = {Behind and beyond the Standard(Ization) Trap},
  author = {Lee, Junesoo},
  year = {2024},
  month = jan,
  journal = {International Review of Public Administration},
  volume = {29},
  number = {1},
  pages = {1--19},
  issn = {1229-4659, 2331-7795},
  doi = {10.1080/12294659.2024.2310899},
  urldate = {2024-08-12},
  abstract = {Standardization, often seen as a means to increase power through uniform working methods, has both benefits and drawbacks. Scholars and practitioners highlight the risk of a `standard(ization) trap', where initial benefits lead to unforeseen costs. This study reviews literature and practices in standardization, identifying confusion between two power sources: substance power, concerning WHETHER to standardize, and decision-making power, dealing with WHO standardizes. It introduces a matrix differentiating these sources, offering insights into standardization methods. This matrix proposes four archetypes of standardization: centralized standardization, centralized destandardization, decentralized standardization, and decentralized destandardization. These archetypes offer theoretical and practical insights for addressing standardization challenges.},
  langid = {english},
  file = {/Users/dkapitan/Zotero/storage/3R555RJ2/Lee - 2024 - Behind and beyond the standard(ization) trap diversifying power sources by differentiating centrali.pdf}
}

@article{leifer1988matching,
  title = {Matching {{Computer-Based Information Systems}} with {{Organizational Structures}}},
  author = {Leifer, Richard},
  year = {1988},
  journal = {MIS Quarterly},
  volume = {12},
  number = {1},
  eprint = {248805},
  eprinttype = {jstor},
  pages = {63--73},
  publisher = {Management Information Systems Research Center, University of Minnesota},
  issn = {0276-7783},
  doi = {10.2307/248805},
  urldate = {2024-08-12},
  abstract = {Results of studies of the organizational impact of computer-based information systems (CBIS) are contradictory and uncertain. One reason is that what is meant by a CBIS differs from one study to another. In an effort to clarify linkages among CBIS designs and organizational contexts of use, a number of CBIS organization matches or "fits" are suggested based upon a four-part categorization of CBIS, consisting of centralized systems, distributed systems, decentralized systems, and stand-alone systems. Appropriate CBIS are then determined for different organizational configurations. The impact of CBIS on organization structure will depend on whether a CBIS structure fit exists. This approach should provide guidance for researchers in discussing CBIS-organization linkages as well as provide practitioners an additional criteria for ensuring CBIS success.},
  file = {/Users/dkapitan/Zotero/storage/JHHZ66SS/Leifer - 1988 - Matching Computer-Based Information Systems with Organizational Structures.pdf}
}

@article{liu2010architectural,
  title = {Architectural Design for Resilience},
  author = {Liu, Dong and Deters, Ralph and Zhang, W. J.},
  year = {2010},
  month = may,
  journal = {Enterprise Information Systems},
  volume = {4},
  number = {2},
  pages = {137--152},
  publisher = {Taylor \& Francis},
  issn = {1751-7575},
  doi = {10.1080/17517570903067751},
  urldate = {2024-08-13},
  abstract = {Resilience has become a new nonfunctional requirement for information systems. Many design decisions have to be made at the architectural level in order to deliver an information system with the resilience property. This paper discusses the relationships between resilience and other architectural properties such as scalability, reliability, and consistency. A corollary is derived from the CAP theorem, and states that it is impossible for a system to have all three properties of consistency, resilience and partition-tolerance. We present seven architectural constraints for resilience. The constraints are elicited from good architectural practices for developing reliable and fault-tolerant systems and the state-of-the-art technologies in distributed computing. These constraints provide a comprehensive reference for architectural design towards resilience.},
  keywords = {fault tolerance,redundancy,reliability,resilience,self-management,service-oriented architecture,software architecture,virtualisation},
  file = {/Users/dkapitan/Zotero/storage/WYLF4IN5/Liu et al. - 2010 - Architectural design for resilience.pdf}
}

@article{liu2020high,
  title = {High {{Performance Computing}} on {{Flat FHIR Files Created}} with the {{New SMART}}/{{HL7 Bulk Data Access Standard}}},
  author = {Liu, Dianbo and Sahu, Ricky and Ignatov, Vlad and Gottlieb, Dan and Mandl, Kenneth D.},
  year = {2020},
  month = mar,
  journal = {AMIA Annual Symposium Proceedings},
  volume = {2019},
  pages = {592--596},
  issn = {1942-597X},
  urldate = {2023-07-04},
  abstract = {The FHIR Bulk Data API is designed to create a uniform capability for population-level exports from clinical systems, into a file format often referred to as ``Flat-FHIR.'' Leveraging the SMART backend services authentication and authorization profile, the approach enables healthcare providers and organizations to define and access cohorts from electronic health records and payor claims data with ``push button'' simplicity--a substantial advance over the current state, where each site of care needs highly skilled extraction transform and load (ETL) efforts.},
  pmcid = {PMC7153160},
  pmid = {32308853},
  file = {/Users/dkapitan/Zotero/storage/XDZCYMA7/Liu et al. - 2020 - High Performance Computing on Flat FHIR Files Crea.pdf}
}

@inproceedings{malm-nicolais2023exploring,
  title = {Exploring the {{Emergence}} of {{Open Platforms}} in {{Healthcare}}: {{Design Considerations}} and {{Experiences}} from an {{Initial Case}} in {{Norwegian Primary Care}}},
  booktitle = {56th {{Hawaii International Conference}} on {{System Sciences}}},
  author = {{Malm-Nicolaisen}, Kristian and Pedersen, Rune and Fagerlund, Asbj{\o}rn Johansen},
  year = {2023},
  abstract = {Despite significant efforts on improving interoperability of health information and lowering socio-technical cost of replacing clinical applications, healthcare organizations and professionals struggle with fragmented and non-interoperable Health Information Technologies. This paper describes the emergence of open platforms, which may alleviate challenges related to interoperability issues, weak integrations, siloed data repositories, and numerous legacy systems within healthcare. Using a proposed platform initiative in Norway, we explore the open platform phenomenon with a socio-technical lens, and highlights four key topics that have produced tension and merits consideration from the involved stakeholders: i) Procurement strategy and vendor neutrality, ii) Ability to facilitate flexible use, iii) The use of standards and separation of data and application, and iv) Strategies for development and governance of standards. We further discuss the related implications and design considerations necessary to support complex patient pathways and provide clinicians more flexible and effective systems.},
  langid = {english},
  file = {/Users/dkapitan/Zotero/storage/5N3G45MB/Malm-Nicolaisen et al. - Exploring the Emergence of Open Platforms in Healt.pdf}
}

@techreport{mambile2023bridging,
  type = {Preprint},
  title = {Bridging the {{Gap}}: {{A Comprehensive Evaluation}} of the {{Government}} of {{Tanzania Hospital Management Information System}} ({{GoTHOMIS}}) through {{Participatory Action Research}}},
  shorttitle = {Bridging the {{Gap}}},
  author = {Mambile, Cesilia and Mwogosi, Augustino},
  year = {2023},
  month = jun,
  institution = {In Review},
  doi = {10.21203/rs.3.rs-3072442/v1},
  urldate = {2024-03-07},
  abstract = {Abstract           This study addresses the implementation and impact of the Government of Tanzania's Hospital Management Information System (GoTHOMIS) using a participatory action research (PAR) approach. Its purpose is to assess the implementation factors, strengths and weaknesses of GoTHOMIS on healthcare services in Tanzania. The research employs a PAR methodology involving stakeholders from healthcare facilities, administrators, and I.T. experts. Data collection methods include document evaluation and interviews with key informants. The findings highlight significant areas for improvement in the implementation process, characterized by a top-down approach and a lack of user participation, hindering the system's successful adoption. Inadequate infrastructure, including network connectivity and outdated hardware, posed further challenges. Compatibility issues with peripheral devices and usability problems were also identified. Despite the challenges, GoTHOMIS demonstrated strengths such as improved accessibility, integration with the MTUHA reporting system, and automation of clinical tasks---weaknesses, including some system components, were only partially automated, which caused inefficiencies in the delivery of healthcare services and failure in integrating with other existing healthcare systems and data sources. Limitations of the study include a focus on selected healthcare facilities, limiting generalizability, and reliance on self-reported data, which may introduce biases. The study's originality lies in applying a PAR approach to assess GoTHOMIS, providing valuable insights into implementation challenges and potential improvements.},
  langid = {english},
  file = {/Users/dkapitan/Zotero/storage/FQ95E6X7/Mambile and Mwogosi - 2023 - Bridging the Gap A Comprehensive Evaluation of th.pdf}
}

@article{mamuye2022health,
  title = {Health Information Exchange Policy and Standards for Digital Health Systems in Africa: {{A}} Systematic Review},
  shorttitle = {Health Information Exchange Policy and Standards for Digital Health Systems in Africa},
  author = {Mamuye, Adane L. and Yilma, Tesfahun M. and Abdulwahab, Ahmad and Broomhead, Sean and Zondo, Phumzule and Kyeng, Mercy and Maeda, Justin and Abdulaziz, Mohammed and Wuhib, Tadesse and Tilahun, Binyam C.},
  year = {2022},
  month = oct,
  journal = {PLOS Digital Health},
  volume = {1},
  number = {10},
  pages = {e0000118},
  publisher = {Public Library of Science},
  issn = {2767-3170},
  doi = {10.1371/journal.pdig.0000118},
  urldate = {2023-06-12},
  abstract = {Lack of interoperability and integration between heterogeneous health systems is a big challenge to realize the potential benefits of eHealth. To best move from siloed applications to interoperable eHealth solutions, health information exchange (HIE) policy and standards are necessary to be established. However, there is no comprehensive evidence on the current status of HIE policy and standards on the African continent. Therefore, this paper aimed to systematically review the status of HIE policy and standards which are currently in practice in Africa. A systematic search of the literature was conducted from Medical Literature Analysis and Retrieval System Online (MEDLINE), Scopus, Web of Science, and Excerpta Medica Database (EMBASE), and a total of 32 papers (21 strategic documents and 11 peer-reviewed papers) were selected based on predefined criteria for synthesis. Results revealed that African countries have paid attention to the development, improvement, adoption, and implementation of HIE architecture for interoperability and standards. Synthetic and semantic interoperability standards were identified for the implementation of HIE in Africa. Based on this comprehensive review, we recommend that comprehensive interoperable technical standards should be set at each national level and should be guided by appropriate governance and legal frameworks, data ownership and use agreements, and health data privacy and security guidelines. On top of the policy issues, there is a need to identify a set of standards (health system standards, communication, messaging standards, terminology/vocabulary standards, patient profile standards, privacy and security, and risk assessment) and implement them throughout all levels of the health system. On top of this, we recommend that the Africa Union (AU) and regional bodies provide the necessary human resource and high-level technical support to African countries to implement HIE policy and standards. To realize the full potential of eHealth in the continent, it is recommended that African countries need to have a common HIE policy, interoperable technical standards, and health data privacy and security guidelines. Currently, there is an ongoing effort by the Africa Centres for Disease Control and Prevention (Africa CDC) towards promoting HIE on the continent. A task force has been established from Africa CDC, Health Information Service Provider (HISP) partners, and African and global HIE subject matter experts to provide expertise and guidance in the development of AU policy and standards for HIE. Although the work is still ongoing, the African Union shall continue to support the implementation of HIE policy and standards in the continent. The authors of this review are currently working under the umbrella of the African Union to develop the HIE policy and standard to be endorsed by the head of states of the Africa Union. As a follow-up publication to this, the result will be published in mid-2022.},
  langid = {english},
  keywords = {Africa,Communication in health care,Computer architecture,Data management,Global health,Health care policy,Health services administration and management,Health systems strengthening},
  file = {/Users/dkapitan/Zotero/storage/E6B963RU/Mamuye et al. - 2022 - Health information exchange policy and standards f.pdf}
}

@misc{managing,
  title = {Managing {{Personal Identifiable Information}} in {{Data Lakes}} {\textbar} {{IEEE Journals}} \& {{Magazine}} {\textbar} {{IEEE Xplore}}},
  urldate = {2024-03-27},
  howpublished = {https://ieeexplore-ieee-org.dianus.libr.tue.nl/abstract/document/10431740},
  file = {/Users/dkapitan/Zotero/storage/N9ZAMIKK/Managing Personal Identifiable Information in Data.pdf;/Users/dkapitan/Zotero/storage/6WA7T56V/10431740.html}
}

@article{mandl2020push,
  title = {Push {{Button Population Health}}: {{The SMART}}/{{HL7 FHIR Bulk Data Access Application Programming Interface}}},
  shorttitle = {Push {{Button Population Health}}},
  author = {Mandl, Kenneth D. and Gottlieb, Daniel and Mandel, Joshua C. and Ignatov, Vladimir and Sayeed, Raheel and Grieve, Grahame and Jones, James and Ellis, Alyssa and Culbertson, Adam},
  year = {2020},
  month = nov,
  journal = {npj Digital Medicine},
  volume = {3},
  number = {1},
  pages = {1--9},
  publisher = {Nature Publishing Group},
  issn = {2398-6352},
  doi = {10.1038/s41746-020-00358-4},
  abstract = {The 21st Century Cures Act requires that certified health information technology have an application programming interface (API) giving access to all data elements of a patient's electronic health record, ``without special effort''. In the spring of 2020, the Office of the National Coordinator of Health Information Technology (ONC) published a rule---21st Century Cures Act Interoperability, Information Blocking, and the ONC Health IT Certification Program---regulating the API requirement along with protections against information blocking. The rule specifies the SMART/HL7 FHIR Bulk Data Access API, which enables access to patient-level data across a patient population, supporting myriad use cases across healthcare, research, and public health ecosystems. The API enables ``push button population health'' in that core data elements can readily and standardly be extracted from electronic health records, enabling local, regional, and national-scale data-driven innovation.},
  copyright = {2020 The Author(s)},
  langid = {english},
  keywords = {Health policy,Outcomes research},
  file = {/Users/dkapitan/Zotero/storage/3JGH9Q26/Mandl et al. - 2020 - Push Button Population Health The SMARTHL7 FHIR .pdf;/Users/dkapitan/Zotero/storage/J3I6PXM2/s41746-020-00358-4.html}
}

@article{mantri2024perspective,
  title = {A Perspective on Digital Health Platform Design and Its Implementation at National Level},
  author = {Mantri, Manisha and Sunder, Gaur and Kadam, Sanjay and Abhyankar, Aditya},
  year = {2024},
  month = apr,
  journal = {Frontiers in Digital Health},
  volume = {6},
  publisher = {Frontiers},
  issn = {2673-253X},
  doi = {10.3389/fdgth.2024.1260855},
  urldate = {2024-04-18},
  abstract = {{$<$}p{$>$}Accessible and affordable health services and products including medicines, vaccines, and public health are an important health agenda of all countries. It is well understood that without digital health technologies, countries will face difficulties in tackling the needs and demands of their population. Global agencies including the World Health Organization (WHO), United Nations (UN), International Telecommunication Union (ITU), etc. have been instrumental in providing various tools, and guidance through digital health strategies in improving health and digital health maturity of the countries. The Digital Health Platform Handbook (DHPH) is a toolkit published by WHO and ITU to help countries create and implement a digital health platform (DHP) to serve as the underlying infrastructure for an interoperable and integrated national digital health system. We apply the foundational principles of DHPH and provide a perspective of DHP components in a layered, enterprise architecture of a digital health infrastructure. India has rolled out the blueprint of its National Digital Health Mission (NDHM) to address the emerging needs for digitization of healthcare in the country. In this paper, we also illustrate the design and implementation of WHO-ITU DHP components at the national level by exploring India's digital health mission implementation utilizing various digital public goods to build a digital health ecosystem in the country.{$<$}/p{$>$}},
  langid = {english},
  keywords = {Digital health platform,India,interoperability,itu,NDHM,Standards,WHO},
  file = {/Users/dkapitan/Zotero/storage/87TGE8HF/Mantri et al. - 2024 - A perspective on digital health platform design and its implementation at national level.pdf}
}

@article{mayar2022resilience,
  title = {Resilience and {{Systems}}---{{A Review}}},
  author = {Mayar, Khalilullah and Carmichael, David G. and Shen, Xuesong},
  year = {2022},
  month = jan,
  journal = {Sustainability},
  volume = {14},
  number = {14},
  pages = {8327},
  publisher = {Multidisciplinary Digital Publishing Institute},
  issn = {2071-1050},
  doi = {10.3390/su14148327},
  urldate = {2024-08-13},
  abstract = {This paper presents, from a systems orientation, a review of the resilience literature since its emergence as an ecological concept in academic parlance in 1973. It argues that much of the resilience literature covers existing ground in that existing engineering systems stability ideas are being reinvented. The review follows modern control systems theory as the comparison framework, where each system, irrespective of its disciplinary association, is represented in terms of inputs, state, and outputs. Modern control systems theory is adopted because of its cohesiveness and universality. The review reveals that resilience can be thought of in terms of adaptive systems and adaptation, where the system has the ability to respond to perturbations and changes through passive and active feedback mechanisms---returning the system state or system form to a starting position or transitioning to another suitable state or form. This systematic and cross-disciplinary review offers the potential for a greater understanding of resilience and the elimination of overlap in the literature, particularly related to terminology.},
  copyright = {http://creativecommons.org/licenses/by/3.0/},
  langid = {english},
  keywords = {adaptive control systems,engineering resilience,resilience,resilience definitions,resilience engineering,socio-ecological resilience,state-space approach,system thinking},
  file = {/Users/dkapitan/Zotero/storage/JA67G99S/Mayar et al. - 2022 - Resilience and Systems—A Review.pdf}
}

@misc{mazumdar2023data,
  title = {The {{Data Lakehouse}}: {{Data Warehousing}} and {{More}}},
  shorttitle = {The {{Data Lakehouse}}},
  author = {Mazumdar, Dipankar and Hughes, Jason and Onofre, J. B.},
  year = {2023},
  month = oct,
  number = {arXiv:2310.08697},
  eprint = {2310.08697},
  primaryclass = {cs},
  publisher = {arXiv},
  urldate = {2024-01-11},
  abstract = {Relational Database Management Systems designed for Online Analytical Processing (RDBMS-OLAP) have been foundational to democratizing data and enabling analytical use cases such as business intelligence and reporting for many years. However, RDBMS-OLAP systems present some well-known challenges. They are primarily optimized only for relational workloads, lead to proliferation of data copies which can become unmanageable, and since the data is stored in proprietary formats, it can lead to vendor lock-in, restricting access to engines, tools, and capabilities beyond what the vendor offers. As the demand for data-driven decision making surges, the need for a more robust data architecture to address these challenges becomes ever more critical. Cloud data lakes have addressed some of the shortcomings of RDBMS-OLAP systems, but they present their own set of challenges. More recently, organizations have often followed a two-tier architectural approach to take advantage of both these platforms, leveraging both cloud data lakes and RDBMS-OLAP systems. However, this approach brings additional challenges, complexities, and overhead. This paper discusses how a data lakehouse, a new architectural approach, achieves the same benefits of an RDBMS-OLAP and cloud data lake combined, while also providing additional advantages. We take today's data warehousing and break it down into implementation independent components, capabilities, and practices. We then take these aspects and show how a lakehouse architecture satisfies them. Then, we go a step further and discuss what additional capabilities and benefits a lakehouse architecture provides over an RDBMS-OLAP.},
  archiveprefix = {arXiv},
  keywords = {Computer Science - Databases},
  file = {/Users/dkapitan/Zotero/storage/IV9Y5T4V/Mazumdar et al. - 2023 - The Data Lakehouse Data Warehousing and More.pdf;/Users/dkapitan/Zotero/storage/AIKBHRKJ/2310.html}
}

@article{mbugua2021adoption,
  title = {Adoption of {{ICT}} to {{Enhance Access}} to {{Healthcare}} in {{Kenya}}},
  author = {Mbugua, Samuel and Korongo, Julia and Joram, Mutai and Chuma Benard, Masese and Nambiro, Alice},
  year = {2021},
  month = apr,
  journal = {IOSR Journal of Computer Engineering},
  volume = {23},
  pages = {45--50},
  doi = {10.9790/0661-2302024550},
  abstract = {Kenya like other developing countries is faced with a burden of disease aggravated by poverty. Communicable and non-communicable diseases are increasing at an alarming rate and straining already overburdened and weak heath systems. Faced with a rapidly growing population, poorly equipped health workforce and meager resources to support the healthcare systems, there is a continuous search for tools to offer better healthcare in these resource constrained settings. ICT for development is one tool that has been adopted to improve access to quality healthcare for populations in resource constrained settings. While the tool has been shown to impact the health care sector positively, the use of ICT has brought in challenges of interoperability and usability of electronic systems in health. In this paper we investigate how Kenya has utilized ICT to spur development in the health sector and the measures she is undertaking to address these challenges. We advance that ICT for development is a tool that needs to be fully exploited by developing countries in order to bridge gaps in healthcare emanating from limited finances, poor infrastructure and an overstretched healthcare workforce.},
  file = {/Users/dkapitan/Zotero/storage/LFVHYGYK/Mbugua et al. - 2021 - Adoption of ICT to Enhance Access to Healthcare in.pdf}
}

@article{mccool2022mobile,
  title = {Mobile {{Health}} ({{mHealth}}) in {{Low-}} and {{Middle-Income Countries}}},
  author = {McCool, Judith and Dobson, Rosie and Whittaker, Robyn and Paton, Chris},
  year = {2022},
  journal = {Annual Review of Public Health},
  volume = {43},
  number = {1},
  pages = {525--539},
  doi = {10.1146/annurev-publhealth-052620-093850},
  urldate = {2023-02-07},
  abstract = {This article reflects on current trends and proposes new considerations for the future of mobile technologies for health (mHealth). Our focus is predominantly on the value of and concerns with regard to the application of digital health within low- and middle-income countries (LMICs). It is in LMICs and marginalized communities that mHealth (within the wider scope of digital health) could be most useful and valuable. Peer-reviewed literature on mHealth in LMICs provides reassurance of this potential, often reflecting on the ubiquity of mobile phones and ever-increasing connectivity globally, reaching remote or otherwise disengaged populations. Efforts to adapt successful programs for LMIC contexts and populations are only just starting to reap rewards. Private-sector investment in mHealth offers value through enhanced capacity and advances in technology as well as the ability to meet increasing consumer demand for real-time, accessible, convenient, and choice-driven health care options. We examine some of the potential considerations associated with a private-sector investment, questioning whether a core of transparency, local ownership, equity, and safety is likely to be upheld in the current environment of health entrepreneurship.},
  pmid = {34648368},
  keywords = {governance,health services,LMICs,low- and middle-income countries,mHealth,mobile,private sector},
  file = {/Users/dkapitan/Zotero/storage/29B6SH98/McCool et al. - 2022 - Mobile Health (mHealth) in Low- and Middle-Income .pdf}
}

@article{mceachen2023enabling,
  title = {{{ENABLING KNOWLEDGE SHARING BY MANAGING DEPENDENCIES AND INTEROPERABILITY BETWEEN INTERLINKED SPATIAL KNOWLEDGE GRAPHS}}},
  author = {McEachen, N. and Lewis, J.},
  year = {2023},
  month = jun,
  journal = {The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences},
  volume = {XLVIII-4-W7-2023},
  pages = {117--124},
  publisher = {Copernicus GmbH},
  issn = {1682-1750},
  doi = {10.5194/isprs-archives-XLVIII-4-W7-2023-117-2023},
  urldate = {2024-04-26},
  abstract = {Knowledge sharing is increasingly being recognized as necessary to address societal, economic, environmental, and public health challenges. This often requires collaboration between federal, local, and tribal governments along with the private sector, nonprofit organizations, and institutions of higher education. To achieve this, there needs to be a move away from data-centric to knowledge sharing architectures, such as a Geospatial Knowledge Infrastructure (GKI). Data from multiple organizations need to be properly contextualized in both space and time to support geographically based planning, decision making, cooperation and coordination. A spatial knowledge graph (SKG) is a useful paradigm for facilitating knowledge sharing and collaboration. However, interoperability between independently developed SKGs from different organizations that reference the same geographies is often not automated in a machine-readable way due to a lack of standardization. This paper outlines an architecture that automates interoperability and dependency management between SKGs as they are formally published by version and period of validity. We are calling this approach a spatial knowledge mesh (SKM), as it is a specialization of the data mesh architecture along with the concept of a common geo-registry to facilitate knowledge sharing more easily. The initial implementation, called GeoPrism Registry, is being developed as an open-source spatial knowledge infrastructure as a platform to help countries meet their NSDI and GKI objectives. It was fist funded and deployed to support ministries of health and is more recently being utilized in GeoPlatform.gov.},
  langid = {english},
  keywords = {Common Geo-Registry,Data Mesh,Graph Repository,Interoperability,Ontology,Spatial Knowledge Graph,Spatial Knowledge Mesh},
  file = {/Users/dkapitan/Zotero/storage/P6FZUD26/McEachen and Lewis - 2023 - ENABLING KNOWLEDGE SHARING BY MANAGING DEPENDENCIE.pdf}
}

@article{mehl2020open,
  title = {Open {{Smart Register Platform}} ({{OpenSRP}})},
  author = {Mehl, Garrett},
  year = {2020},
  month = oct,
  journal = {mHealth Compendium},
  volume = {5},
  pages = {42--43},
  urldate = {2023-01-21},
  abstract = {The Open Smart Register Platform (OpenSRP) can run on any Android device and integrates previously dicrete proven innovations in mHealth. OpenSRP complements other widely-deployed information technology solutions, including DHIS2 and OpenMRS.},
  langid = {english},
  annotation = {Accepted: 2020-10-14T10:19:22Z},
  file = {/Users/dkapitan/Zotero/storage/AYEIEQ8L/Garrett Mehl - 2020 - Open Smart Register Platform (OpenSRP).pdf}
}

@article{mehl2021who,
  title = {{{WHO SMART}} Guidelines: Optimising Country-Level Use of Guideline Recommendations in the Digital Age},
  shorttitle = {{{WHO SMART}} Guidelines},
  author = {Mehl, Garrett and Tun{\c c}alp, {\"O}zge and Ratanaprayul, Natschja and Tamrat, Tigest and Barreix, Mar{\'i}a and Lowrance, David and Bartolomeos, Kidist and Say, Lale and Kostanjsek, Nenad and Jakob, Robert and Grove, John and Mariano, Bernardo and Swaminathan, Soumya},
  year = {2021},
  month = apr,
  journal = {The Lancet Digital Health},
  volume = {3},
  number = {4},
  pages = {e213-e216},
  publisher = {Elsevier},
  issn = {2589-7500},
  doi = {10.1016/S2589-7500(21)00038-8},
  urldate = {2023-06-21},
  langid = {english},
  pmid = {33610488},
  file = {/Users/dkapitan/Zotero/storage/ZQH6V9GJ/Mehl et al. - 2021 - WHO SMART guidelines optimising country-level use.pdf}
}

@article{mehl2023fullstac,
  title = {A Full-{{STAC}} Remedy for Global Digital Health Transformation: Open Standards, Technologies, Architectures and Content},
  shorttitle = {A Full-{{STAC}} Remedy for Global Digital Health Transformation},
  author = {Mehl, Garrett L and Seneviratne, Martin G and Berg, Matt L and Bidani, Suhel and Distler, Rebecca L and Gorgens, Marelize and Kallander, Karin E and Labrique, Alain B and Landry, Mark S and Leitner, Carl and {Lubell-Doughtie}, Peter B and Marcelo, Alvin D and Matias, Yossi and Nelson, Jennifer and Nguyen, Von and Nsengimana, Jean Philbert and Orton, Maeghan and Otzoy Garcia, Daniel R and Oyaole, Daniel R and Ratanaprayul, Natschja and Roth, Susann and Schaefer, Merrick P and Settle, Dykki and Tang, Jing and {Tien-Wahser}, Barakissa and Wanyee, Steven and Hersch, Fred},
  year = {2023},
  month = jan,
  journal = {Oxford Open Digital Health},
  volume = {1},
  pages = {oqad018},
  issn = {2754-4591},
  doi = {10.1093/oodh/oqad018},
  urldate = {2024-02-09},
  abstract = {The global digital health ecosystem is project-centric: point solutions are developed for vertical health programs and financed through vertical funding allocations. This results in data fragmentation and technology lock-in, compromising health care delivery. A convergence of trends enabled by interoperability and digital governance makes possible a shift towards person-focused health. Together, open Standards, open Technologies, open Architectures and open Content represent a next-generation `full-STAC' remedy for digital health transformation. Local developers and implementers can avoid reinventing the wheel, and instead build digital tools suited to local needs---where data travels with an individual over time, evidence-based practice is easily integrated, and insights are gleaned from harmonized data. This is the culmination of the vision endorsed by 194 WHO Member States in the Global Strategy on Digital Health 2020 to 2025.},
  file = {/Users/dkapitan/Zotero/storage/4D3EIB6H/Mehl et al. - 2023 - A full-STAC remedy for global digital health trans.pdf;/Users/dkapitan/Zotero/storage/9ILKUCUU/7475299.html}
}

@incollection{menard2014contribution,
  title = {The {{Contribution}} of {{Douglass North}} to {{New Institutional Economics}}},
  booktitle = {Institutions, {{Property Rights}}, and {{Economic Growth}}},
  author = {M{\'e}nard, Claude and Shirley, Mary M.},
  editor = {Galiani, Sebastian and Sened, Itai},
  year = {2014},
  month = apr,
  edition = {1},
  pages = {11--29},
  publisher = {Cambridge University Press},
  doi = {10.1017/CBO9781107300361.003},
  urldate = {2024-08-28},
  abstract = {Douglass North, along with Ronald Coase and Oliver Williamson, transformed the early intuitions of new institutional economics into powerful conceptual and analytical tools that spawned a robust base of empirical research. NIE arose in response to questions not well explained by standard neoclassical models, such as make or buy and why rich or poor? Today NIE is a success story by many measures: four Nobel laureates in under 20 years, increasing penetration of mainstream journals, and significant impact on major policy debates from anti-trust law to development aid. This paper provides a succinct overview of North's evolving ideas about institutions and explains how North's work shaped the emerging field of new institutional economics and had a potent impact on economics and the social sciences more broadly. North provides a powerful example of how persistent and well placed confidence and hard work can productively transform the status quo. North's influence continues strong and his enthusiasm for exploring new frontiers and cooperating across artificial academic boundaries has never waned.},
  isbn = {978-1-107-30036-1 978-1-107-04155-4},
  langid = {english},
  file = {/Users/dkapitan/Zotero/storage/NBJ7ZEPU/Ménard and Shirley - 2014 - The Contribution of Douglass North to New Institut.pdf}
}

@inproceedings{morales2021blockgraph,
  title = {Blockgraph Proof-of-Concept},
  booktitle = {Proceedings of the {{SIGCOMM}} '21 {{Poster}} and {{Demo Sessions}}},
  author = {Morales, David Cordova and Velloso, Pedro and Guerre, Alexandre and Nguyen, Thi-Mai-Trang and Pujolle, Guy and Alagha, Khaldoun and Dua, Guillaume},
  year = {2021},
  month = aug,
  pages = {82--84},
  publisher = {ACM},
  address = {Virtual Event},
  doi = {10.1145/3472716.3472866},
  urldate = {2024-02-12},
  abstract = {Blockgraph is a new structure of blockchain in which the blocks are interconnected in the form of a graph instead of a chain. Blockgraph has been designed to enable the use of blockchain in mobile adhoc networks and mesh networks by dealing with the problem of network partition due to node mobility. This paper presents a proof of the blockgraph concept using a testbed composed of five mesh routers. The demonstration shows that the blockgraph is created and maintained by the participant nodes in case of network split and merge.},
  isbn = {978-1-4503-8629-6},
  langid = {english},
  file = {/Users/dkapitan/Zotero/storage/HH2TM5C2/Morales et al. - 2021 - Blockgraph proof-of-concept.pdf}
}

@article{morris2023call,
  title = {A {{Call}} to {{Reconsider}} a {{Nationwide Electronic Health Record System}}: {{Correcting}} the {{Failures}} of the {{National Program}} for {{IT}}},
  shorttitle = {A {{Call}} to {{Reconsider}} a {{Nationwide Electronic Health Record System}}},
  author = {Morris, James Seymour},
  year = {2023},
  month = dec,
  journal = {JMIR Medical Informatics},
  volume = {11},
  number = {1},
  pages = {e53112},
  publisher = {JMIR Publications Inc., Toronto, Canada},
  doi = {10.2196/53112},
  urldate = {2024-04-18},
  abstract = {The National Programme for IT (NPfIT) was launched in 2005 to implement seven nationwide IT services across the National Health Service (NHS). Despite the success of many of these so-called ``deliverables'', the establishment of a single nationwide electronic health record (EHR) system never fully materialised. Healthcare practitioners are all too often left without access to large sections of their patients' medical records due to their being recording on any one of a plethora of alternative EHR systems. This not only limits their ability to make well-informed clinical decisions, but also the quality of care they are able to provide. This article evaluates the medical, economic and bureaucratic implications of an NHS-wide EHR system before exploring how the shortcomings of the NPfIT should be addressed when attempting to introduce such a system in future.},
  copyright = {This is an open-access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work, first published JMIR Medical Informatics, is properly cited. The complete bibliographic information, a link to the original publication on https://medinform.jmir.org/, as well as this copyright and license information must be included.},
  langid = {english},
  file = {/Users/dkapitan/Zotero/storage/IY5ZSMJ8/Morris - 2023 - A Call to Reconsider a Nationwide Electronic Healt.pdf;/Users/dkapitan/Zotero/storage/KRPRRX8R/e53112.html}
}

@article{mrema2021application,
  title = {Application of {{Digital Platform}} to {{Enhance Quality Improvement}} in {{Momcare Facilities}} in {{Manyara}}},
  author = {Mrema, Anunsiatha},
  year = {2021},
  month = jul,
  journal = {AIJR Abstracts},
  publisher = {AIJR Publisher},
  urldate = {2023-02-03},
  abstract = {This book contains the abstracts of the papers/posters presented at the Tanzania Health Summit 2020 (THS-2020) Organized by the Ministry of Health Community Development, Gender, Elderly and Children (MoHCDGEC); President Office Regional Administration and Local Government (PORALG); Ministry of Health, Social Welfare, Elderly, Gender, and Children Zanzibar; Association of Private Health Facilities in Tanzania (APHFTA); National Muslim Council of Tanzania (BAKWATA); Christian Social Services Commission (CSSC); \&amp; Tindwa Medical and Health Services (TMHS) held on 25--26 November 2020. The Tanzania Health Summit is the annual largest healthcare platform in Tanzania that attracts more than 1000 participants, national and international experts, from policymakers, health researchers, public health professionals, health insurers, medical doctors, nurses, pharmacists, private health investors, supply chain experts, and the civil society. During the three-day summit, stakeholders and decision-makers from every field in healthcare work together to find solutions to the country's and regional health challenges and set the agenda for a healthier future. Summit Title: Tanzania Health SummitSummit Acronym: THS-2020Summit Date: 25--26 November 2020Summit Location: St. Gasper Hotel and Conference Centre in Dodoma, TanzaniaSummit Organizers: Ministry of Health Community Development, Gender, Elderly and Children (MoHCDGEC); President Office Regional Administration and Local Government (PORALG); Ministry of Health, Social Welfare, Elderly, Gender and Children Zanzibar; Association of Private Health Facilities in Tanzania (APHFTA); National Muslim Council of Tanzania (BAKWATA); Christian Social Services Commission (CSSC); \&amp; Tindwa Medical and Health Services (TMHS).},
  copyright = {\#\#submission.copyrightStatement\#\#},
  isbn = {9788194784395},
  langid = {english},
  file = {/Users/dkapitan/Zotero/storage/S95SG6AQ/Mrema - 2021 - Application of Digital Platform to Enhance Quality.pdf}
}

@misc{mucha2020artificial,
  type = {{{SSRN Scholarly Paper}}},
  title = {Artificial {{Intelligence Platforms}} -- {{A New Research Agenda}} for {{Digital Platform Economy}}},
  author = {Mucha, Tomasz and Seppala, Timo},
  year = {2020},
  month = feb,
  number = {3532937},
  address = {Rochester, NY},
  doi = {10.2139/ssrn.3532937},
  urldate = {2024-08-27},
  abstract = {Three out of nine of S\&P500 digital platform companies stand out as building own artificial intelligence (AI) platforms. There is overwhelming empirical evidence of AI technologies are being central to running a digital platform business. However, the current research agenda is not directing researchers to study AI technologies in the context of digital platforms. We have divided the proposed AI platforms research agenda as follows: The first set of questions we propose relates to an overall conceptualization of AI platforms. Thereafter, we recognize specific aspects of AI platforms, which need to be investigated in detail to gain understanding that is more complete. The second set of questions we propose relates to understanding the dynamics between AI platforms and the broader socio-economic context. This topic might be particularly relevant to economies of countries without indigenous AI platforms. Our paper builds on the proposition that AI is a general-purpose technology, which by itself carries properties of a digital platform.},
  langid = {english},
  keywords = {AI platforms,Artificial Intelligence,Platform Economy,Platforms,Research agenda},
  file = {/Users/dkapitan/Zotero/storage/32B69SXT/Mucha and Seppala - 2020 - Artificial Intelligence Platforms – A New Research.pdf}
}

@article{muinga2020digital,
  title = {Digital Health {{Systems}} in {{Kenyan Public Hospitals}}: A Mixed-Methods Survey},
  shorttitle = {Digital Health {{Systems}} in {{Kenyan Public Hospitals}}},
  author = {Muinga, Naomi and Magare, Steve and Monda, Jonathan and English, Mike and Fraser, Hamish and Powell, John and Paton, Chris},
  year = {2020},
  month = jan,
  journal = {BMC medical informatics and decision making},
  volume = {20},
  number = {1},
  pages = {2},
  issn = {1472-6947},
  doi = {10.1186/s12911-019-1005-7},
  abstract = {BACKGROUND: As healthcare facilities in Low- and Middle-Income Countries adopt digital health systems to improve hospital administration and patient care, it is important to understand the adoption process and assess the systems' capabilities. This survey aimed to provide decision-makers with information on the digital health systems landscape and to support the rapidly developing digital health community in Kenya and the region by sharing knowledge. METHODS: We conducted a survey of County Health Records Information Officers (CHRIOs) to determine the extent to which digital health systems in public hospitals that serve as internship training centres in Kenya are adopted. We conducted site visits and interviewed hospital administrators and end users who were at the facility on the day of the visit. We also interviewed digital health system vendors to understand the adoption process from their perspective. Semi-structured interview guides adapted from the literature were used. We identified emergent themes using a thematic analysis from the data. RESULTS: We obtained information from 39 CHRIOs, 58 hospital managers and system users, and 9 digital health system vendors through semi-structured interviews and completed questionnaires. From the survey, all facilities mentioned purchased a digital health system primarily for administrative purposes. Radiology and laboratory management systems were commonly standalone systems and there were varying levels of interoperability within facilities that had multiple systems. We only saw one in-patient clinical module in use. Users reported on issues such as system usability, inadequate training, infrastructure and system support. Vendors reported the availability of a wide range of modules, but implementation was constrained by funding, prioritisation of services, users' lack of confidence in new technologies and lack of appropriate data sharing policies. CONCLUSION: Public hospitals in Kenya are increasingly purchasing systems to support administrative functions and this study highlights challenges faced by hospital users and vendors. Significant work is required to ensure interoperability of systems within hospitals and with other government services. Additional studies on clinical usability and the workflow fit of digital health systems are required to ensure efficient system implementation. However, this requires support from key stakeholders including the government, international donors and regional health informatics organisations.},
  langid = {english},
  pmcid = {PMC6945428},
  pmid = {31906932},
  keywords = {Digital health,Electronic health records,Health,Health management information systems,Hospitals Public,Humans,Kenya,Medical Informatics,Survey,Surveys and Questionnaires},
  file = {/Users/dkapitan/Zotero/storage/N876NMTX/Muinga et al. - 2020 - Digital health Systems in Kenyan Public Hospitals.pdf}
}

@article{mullie2023coda,
  title = {{{CODA}}: An Open-Source Platform for Federated Analysis and Machine Learning on Distributed Healthcare Data},
  shorttitle = {{{CODA}}},
  author = {Mullie, Louis and Afilalo, Jonathan and Archambault, Patrick and Bouchakri, Rima and Brown, Kip and Buckeridge, David L and Cavayas, Yiorgos Alexandros and Turgeon, Alexis F and Martineau, Denis and Lamontagne, Fran{\c c}ois and Lebrasseur, Martine and Lemieux, Renald and Li, Jeffrey and Sauthier, Micha{\"e}l and {St-Onge}, Pascal and Tang, An and Witteman, William and Chass{\'e}, Micha{\"e}l},
  year = {2023},
  month = dec,
  journal = {Journal of the American Medical Informatics Association},
  pages = {ocad235},
  issn = {1527-974X},
  doi = {10.1093/jamia/ocad235},
  urldate = {2024-01-08},
  abstract = {Distributed computations facilitate multi-institutional data analysis while avoiding the costs and complexity of data pooling. Existing approaches lack crucial features, such as built-in medical standards and terminologies, no-code data visualizations, explicit disclosure control mechanisms, and support for basic statistical computations, in addition to gradient-based optimization capabilities.We describe the development of the Collaborative Data Analysis (CODA) platform, and the design choices undertaken to address the key needs identified during our survey of stakeholders. We use a public dataset (MIMIC-IV) to demonstrate end-to-end multi-modal FL using CODA. We assessed the technical feasibility of deploying the CODA platform at 9 hospitals in Canada, describe implementation challenges, and evaluate its scalability on large patient populations.The CODA platform was designed, developed, and deployed between January 2020 and January 2023. Software code, documentation, and technical documents were released under an open-source license. Multi-modal federated averaging is illustrated using the MIMIC-IV and MIMIC-CXR datasets. To date, 8 out of the 9 participating sites have successfully deployed the platform, with a total enrolment of \&gt;1M patients. Mapping data from legacy systems to FHIR was the biggest barrier to implementation.The CODA platform was developed and successfully deployed in a public healthcare setting in Canada, with heterogeneous information technology systems and capabilities. Ongoing efforts will use the platform to develop and prospectively validate models for risk assessment, proactive monitoring, and resource usage. Further work will also make tools available to facilitate migration from legacy formats to FHIR and DICOM.},
  file = {/Users/dkapitan/Zotero/storage/8Q7H7F9E/Mullie et al. - 2023 - CODA an open-source platform for federated analys.pdf;/Users/dkapitan/Zotero/storage/9WIQCS33/7486840.html}
}

@misc{national,
  title = {National {{Health Authority}} ({{NHA}}) Invites Participation on the `{{National Health Claims Exchange}} ({{HCX}})-{{Sandbox}}' under {{Ayushman Bharat Digital Mission}} ({{ABDM}})},
  urldate = {2024-03-07},
  abstract = {The National Health Authority (NHA) invites contributors and developers from the open community, esp},
  howpublished = {https://pib.gov.in/pib.gov.in/Pressreleaseshare.aspx?PRID=1917688},
  file = {/Users/dkapitan/Zotero/storage/4LJB7KKF/PressReleasePage.html}
}

@article{neumark2021digital,
  title = {Digital {{Health}} in {{East Africa}}: {{Innovation}}, {{Experimentation}} and the {{Market}}},
  shorttitle = {Digital {{Health}} in {{East Africa}}},
  author = {Neumark, Tom and Prince, Ruth J.},
  year = {2021},
  month = jul,
  journal = {Global Policy},
  volume = {12},
  number = {S6},
  pages = {65--74},
  issn = {1758-5880, 1758-5899},
  doi = {10.1111/1758-5899.12990},
  urldate = {2023-02-03},
  abstract = {Across East Africa, mobile phones and tablets are increasingly sitting in the hands of community health workers, clinicians, managers and patients. They are being used for a widening range of functions from diagnostics to health insurance to treatment advice, generating hopes for new healthcare futures and establishing the region as an emerging hub of experimentation in digital health. Drawing on our on-going ethnographic and anthropological research in Kenya and Tanzania, this article explores the dynamic, varied, experimental, and increasingly financialised terrain of formal digital health projects. While innovation in digital health is a growing feature of healthcare across the globe, in East Africa it is entering into a region already long characterised by NGOised, fragmented and vertical healthcare systems and heavy dependence on foreign capital. This presents challenges to efforts, including the WHO's Universal Health Coverage agenda, to foster national and equitable public healthcare systems. In exploring these issues, we recognise the power, and often deleterious effects, of financial capital that foregrounds markets in global digital health, but we also open space for a (still critical) recognition of East African-led digital and data technology movements.},
  langid = {english},
  file = {/Users/dkapitan/Zotero/storage/SQRGP7U8/Neumark and Prince - 2021 - Digital Health in East Africa Innovation, Experim.pdf}
}

@article{ngugi2021multivariate,
  title = {A Multivariate Statistical Evaluation of Actual Use of Electronic Health Record Systems Implementations in {{Kenya}}},
  author = {Ngugi, Philomena and Babic, Ankica and Were, Martin C.},
  year = {2021},
  month = sep,
  journal = {PLOS ONE},
  volume = {16},
  number = {9},
  pages = {e0256799},
  publisher = {Public Library of Science},
  issn = {1932-6203},
  doi = {10.1371/journal.pone.0256799},
  urldate = {2024-07-19},
  abstract = {Background Health facilities in developing countries are increasingly adopting Electronic Health Records systems (EHRs) to support healthcare processes. However, only limited studies are available that assess the actual use of the EHRs once adopted in these settings. We assessed the state of the 376 KenyaEMR system (national EHRs) implementations in healthcare facilities offering HIV services in Kenya. Methods The study focused on seven EHRs use indicators. Six of the seven indicators were programmed and packaged into a query script for execution within each KenyaEMR system (KeEMRs) implementation to collect monthly server-log data for each indicator for the period 2012--2019. The indicators included: Staff system use, observations (clinical data volume), data exchange, standardized terminologies, patient identification, and automatic reports. The seventh indicator (EHR variable Completeness) was derived from routine data quality report within the EHRs. Data were analysed using descriptive statistics, and multiple linear regression analysis was used to examine how individual facility characteristics affected the use of the system. Results 213 facilities spanning 19 counties participated in the study. The mean number of authorized users who actively used the KeEMRs was 18.1\% (SD = 13.1\%, p{$<$}0.001) across the facilities. On average, the volume of clinical data (observations) captured in the EHRs was 3363 (SD = 4259). Only a few facilities(14.1\%) had health data exchange capability. 97.6\% of EHRs concept dictionary terms mapped to standardized terminologies such as CIEL. Within the facility EHRs, only 50.5\% (SD = 35.4\%, p{$<$} 0.001) of patients had the nationally-endorsed patient identifier number recorded. Multiple regression analysis indicated the need for improvement on the mode of EHRs use of implementation. Conclusion The standard EHRs use indicators can effectively measure EHRs use and consequently determine success of the EHRs implementations. The results suggest that most of the EHRs use areas assessed need improvement, especially in relation to active usage of the system and data exchange readiness.},
  langid = {english},
  keywords = {Electronic medical records,Health care facilities,HIV,Kenya,Linear regression analysis,Low and middle income countries,Statistical distributions,Systematic reviews},
  file = {/Users/dkapitan/Zotero/storage/968HMHZG/Ngugi et al. - 2021 - A multivariate statistical evaluation of actual us.pdf}
}

@misc{nhcx,
  title = {{{NHCX Profiles}} - {{FHIR Implementation Guide}} for {{ABDM}} v5.0.0},
  urldate = {2024-01-18},
  howpublished = {https://nrces.in/ndhm/fhir/r4/hcx-profile.html},
  file = {/Users/dkapitan/Zotero/storage/T2TPL7FT/hcx-profile.html}
}

@article{north2023economic,
  title = {Economic {{Performance Through Time}}},
  author = {North, Douglass C},
  year = {2023},
  langid = {english},
  file = {/Users/dkapitan/Zotero/storage/AZ95R37C/North - 2023 - Economic Performance Through Time.pdf}
}

@article{northlimited,
  title = {Limited {{Access Orders}}: {{Rethinking}} the {{Problems}} of {{Development}} and {{Violence}}},
  author = {North, Douglass C and Wallis, John Joseph and Webb, Steven B and Weingast, Barry R},
  abstract = {The paper lays out a new framework for understanding problems of development. It emphasizes that all societies must solve the problem of violence and distinguishes between two ways in which societies solve this problem. Limited access orders, covering most developing countries today, solve the problem of violence by granting political elites privileged control over parts of the economy, each getting some share of the rents. Since outbreaks of violence reduce the rents, elite factions have incentives to refrain from violence most of the time. Stability of the rents and thus of the social order requires limiting access and competition. In contrast, open access orders, which dominate the modern developed world, control the problem of violence through open access and competition. The framework provides a new view of development. It shows that transplanting institutions from open access orders into limited access orders -- such as markets, elections, and corporate law -- often do not have their intended effect because the institutions work differently under limited access than open access. When development policy advice threatens the logic of stability in limited access orders, these societies often resist or sabotage the recommended measures.},
  langid = {english},
  file = {/Users/dkapitan/Zotero/storage/6FDVZW35/North et al. - Limited Access Orders Rethinking the Problems of .pdf}
}

@article{nsaghurwe2021one,
  title = {One Country's Journey to Interoperability: {{Tanzania}}'s Experience Developing and Implementing a National Health Information Exchange},
  shorttitle = {One Country's Journey to Interoperability},
  author = {Nsaghurwe, Alpha and Dwivedi, Vikas and Ndesanjo, Walter and Bamsi, Haji and Busiga, Moses and Nyella, Edwin and Massawe, Japhet Victor and Smith, Dasha and Onyejekwe, Kate and Metzger, Jonathan and Taylor, Patricia},
  year = {2021},
  month = apr,
  journal = {BMC Medical Informatics and Decision Making},
  volume = {21},
  number = {1},
  pages = {139},
  issn = {1472-6947},
  doi = {10.1186/s12911-021-01499-6},
  urldate = {2023-06-01},
  abstract = {Robust, flexible, and integrated health information (HIS) systems are essential to achieving national and international goals in health and development. Such systems are still uncommon in most low and middle income countries. This article describes a first-phase activity in Tanzania to integrate the country's vertical health management information system with the help of an interoperability layer that enables cross-program data exchange.},
  keywords = {Architecture,Governance,Health,Interoperability,Standards},
  file = {/Users/dkapitan/Zotero/storage/YNEPA9TZ/Nsaghurwe et al. - 2021 - One country's journey to interoperability Tanzani.pdf;/Users/dkapitan/Zotero/storage/7XW5ART6/s12911-021-01499-6.html}
}

@article{nyangena2021maturity,
  title = {Maturity Assessment of {{Kenya}}'s Health Information System Interoperability Readiness},
  author = {Nyangena, Job and Rajgopal, Rohini and Ombech, Elizabeth Adhiambo and Oloo, Enock and Luchetu, Humphrey and Wambugu, Sam and Kamau, Onesmus and Nzioka, Charles and Gwer, Samson and Ndiritu Ndirangu, Moses},
  year = {2021},
  month = jun,
  journal = {BMJ Health \& Care Informatics},
  volume = {28},
  number = {1},
  pages = {e100241},
  issn = {2632-1009},
  doi = {10.1136/bmjhci-2020-100241},
  urldate = {2024-03-25},
  abstract = {Background{\enspace} The use of digital technology in healthcare promises to improve quality of care and reduce costs over time. This promise will be difficult to attain without interoperability: facilitating seamless health information exchange between the deployed digital health information systems (HIS). Objective{\enspace} To determine the maturity readiness of the interoperability capacity of Kenya's HIS. Methods{\enspace} We used the HIS Interoperability Maturity Toolkit, developed by MEASURE Evaluation and the Health Data Collaborative's Digital Health and Interoperability Working Group. The assessment was undertaken by eHealth stakeholder representatives primarily from the Ministry of Health's Digital Health Technical Working Group. The toolkit focused on three major domains: leadership and governance, human resources and technology. Results{\enspace} Most domains are at the lowest two levels of maturity: nascent or emerging. At the nascent level, HIS activities happen by chance or represent isolated, ad hoc efforts. An emerging maturity level characterises a system with defined HIS processes and structures. However, such processes are not systematically documented and lack ongoing monitoring mechanisms. Conclusion{\enspace} None of the domains had a maturity level greater than level 2 (emerging). The subdomains of governance structures for HIS, defined national enterprise architecture for HIS, defined technical standards for data exchange, nationwide communication network infrastructure, and capacity for operations and maintenance of hardware attained higher maturity levels. These findings are similar to those from interoperability maturity assessments done in Ghana and Uganda.},
  langid = {english},
  file = {/Users/dkapitan/Zotero/storage/ZWI3FCWB/Nyangena et al. - 2021 - Maturity assessment of Kenya’s health information .pdf}
}

@article{ochieng2024exploring,
  title = {Exploring the Implementation of an {{SMS-based}} Digital Health Tool on Maternal and Infant Health in Informal Settlements},
  author = {Ochieng', Sharon and Hariharan, Nisha and Abuya, Timothy and Okondo, Chantalle and Ndwiga, Charity and Warren, Charlotte E. and Wickramanayake, Anneka and Rajasekharan, Sathyanath},
  year = {2024},
  month = mar,
  journal = {BMC Pregnancy and Childbirth},
  volume = {24},
  number = {1},
  pages = {222},
  issn = {1471-2393},
  doi = {10.1186/s12884-024-06373-7},
  urldate = {2024-09-06},
  abstract = {The rapid urbanization of Kenya has led to an increase in the growth of informal settlements. There are challenges with access to maternal, newborn, and child health (MNCH) services and higher maternal mortality rates in settlements. The Kuboresha Afya Mitaani (KAM) study aimed to improve access to MNCH services. We evaluate one component of the KAM study, PROMPTS (Promoting Mothers through Pregnancy and Postpartum), an innovative digital health intervention aimed at improving MNCH outcomes. PROMPTS is a two-way AI-enabled SMS-based platform that sends messages to pregnant and postnatal mothers based on pregnancy stage, and connects mothers with a clinical help desk to respond and refer urgent cases in minutes.},
  langid = {english},
  keywords = {Antenatal care,Digital health,Informal settlements,Kenya,Maternal health,Medical Ethics,Postnatal care},
  file = {/Users/dkapitan/Zotero/storage/8V2RUINK/Ochieng’ et al. - 2024 - Exploring the implementation of an SMS-based digit.pdf}
}

@article{ogundaini2022systematic,
  title = {Systematic Review: {{Decentralised}} Health Information Systems Implementation in Sub-{{Saharan Africa}}},
  shorttitle = {Systematic Review},
  author = {Ogundaini, Oluwamayowa O. and Achieng, Mourine S.},
  year = {2022},
  journal = {Journal for Transdisciplinary Research in Southern Africa},
  volume = {18},
  number = {1},
  pages = {1--10},
  issn = {2415-2005},
  doi = {10.4102/td.v18i1.1216},
  urldate = {2024-08-12},
  file = {/Users/dkapitan/Zotero/storage/9TTGHB3P/Ogundaini and Achieng - 2022 - Systematic review Decentralised health informatio.pdf}
}

@misc{ohie_shr_planningandimplementationguidev1,
  title = {{{OHIE}}\_{{SHR}}\_{{PlanningandImplementationGuideV1}}.0},
  journal = {Google Docs},
  urldate = {2024-08-27},
  abstract = {OHIE Shared Health Record Planning and Implementation Guide       Table of Contents Introduction Shared Health Record Background Key Functions of the Shared Health Record Purpose and Structure of the Guide Community Engagement Step 1: Analyze the Environment Identify Stakeholders 1.2   Ident...},
  howpublished = {https://docs.google.com/document/d/1as24q7-XHHM9FFa5s5xSbn38JHD7l6T3-9WAZqh9xks/edit?usp=embed\_facebook},
  langid = {british},
  file = {/Users/dkapitan/Zotero/storage/JI5Y2CIC/edit.html}
}

@misc{ohie2023unconference,
  title = {{{OHIE23 Unconference}} 101},
  year = {2023},
  month = nov,
  urldate = {2024-01-23},
  file = {/Users/dkapitan/Zotero/storage/983XN7PC/OHIE23 Unconference 101.pdf;/Users/dkapitan/Zotero/storage/XM8V7T74/OHIE23 Unconference 101.pdf}
}

@misc{ohienigeria,
  title = {Nigeria {{Data Exchange Architecture}} for the {{National Data Repository}}},
  journal = {OpenHIE},
  urldate = {2024-01-22},
  langid = {american},
  file = {/Users/dkapitan/Zotero/storage/CKHPQ67N/nigeria-data-exchange-architecture-for-the-national-data-repository.html}
}

@article{omotosho2019current,
  title = {Current {{State}} of {{ICT}} in {{Healthcare Delivery}} in {{Developing Countries}}},
  author = {Omotosho, Adebayo and Ayegba, Peace and Emuoyibofarhe, Justice and Meinel, Christoph},
  year = {2019},
  month = may,
  journal = {International Journal of Online and Biomedical Engineering (iJOE)},
  volume = {15},
  number = {08},
  pages = {91--107},
  issn = {2626-8493},
  doi = {10.3991/ijoe.v15i08.10294},
  urldate = {2024-03-08},
  abstract = {Electronic health is one of the most popular applications of information and communication technologies and it has contributed immensely to health delivery through the provision of quality health service and ubiquitous access at a lower cost. Even though this mode of health service is increasingly becoming known or used in developing nations, these countries are faced with a myriad of challenges when implementing and deploying e-health services on both small and large scale. It is estimated that the Africa population alone carries the highest percentage of the world's global diseases despite its certain level of e-health adoption. This paper aims at analyzing the progress so far and the current state of e-health in developing countries particularly Africa and propose a framework for further improvement.},
  copyright = {Copyright (c) 2019 Adebayo Omotosho, Peace Ayegba, Justice Emuoyibofarhe, Christoph Meinel},
  langid = {english},
  keywords = {developing countries,e-health,framework,healthcare,ICT},
  file = {/Users/dkapitan/Zotero/storage/JZ62JG8M/Omotosho et al. - 2019 - Current State of ICT in Healthcare Delivery in Dev.pdf}
}

@misc{onnx,
  title = {{{ONNX}} v1.15.0},
  year = {2023},
  month = oct,
  urldate = {2024-02-14},
  howpublished = {https://onnx.ai/},
  file = {/Users/dkapitan/Zotero/storage/H63FVG4K/onnx.ai.html}
}

@misc{openhie,
  title = {{{OpenHIE Framework}} v5.2-En},
  year = {2024},
  month = aug,
  journal = {OpenHIE},
  urldate = {2024-08-27},
  abstract = {OpenHIE is a community of individuals who strive to develop health information exchanges that improve patient care, health, and so much more.},
  howpublished = {https://ohie.org/},
  langid = {american},
  file = {/Users/dkapitan/Zotero/storage/55NPDMZ3/ohie.org.html}
}

@techreport{organization2018classification,
  title = {Classification of {{Digital Health Interventions}} v1.0: {{A}} Shared Language to Describe the Uses of Digital Technology for Health},
  shorttitle = {Classification of {{Digital Health Interventions}} v1.0},
  author = {Organization, World Health},
  year = {2018},
  eprint = {resrep33226},
  eprinttype = {jstor},
  institution = {World Health Organization},
  urldate = {2024-04-18},
  file = {/Users/dkapitan/Zotero/storage/GCXCVEDF/Organization - 2018 - Classification of Digital Health Interventions v1..pdf}
}

@misc{osi2024open,
  title = {The {{Open Source AI Definition}} v0.0.9},
  year = {2024},
  month = aug,
  journal = {HackMD},
  urldate = {2024-08-27},
  abstract = {\# The Open Source AI Definition \#\#\# version 0.0.9 :::info :information\_source: This document follows},
  howpublished = {https://hackmd.io/@opensourceinitiative/osaid-0-0-9},
  langid = {english},
  file = {/Users/dkapitan/Zotero/storage/AJQAH36Y/osaid-0-0-9.html}
}

@book{otto2022designing,
  title = {Designing {{Data Spaces}}: {{The Ecosystem Approach}} to {{Competitive Advantage}}},
  shorttitle = {Designing {{Data Spaces}}},
  editor = {Otto, Boris and Ten Hompel, Michael and Wrobel, Stefan},
  year = {2022},
  publisher = {Springer International Publishing},
  address = {Cham},
  doi = {10.1007/978-3-030-93975-5},
  urldate = {2024-01-23},
  isbn = {978-3-030-93974-8 978-3-030-93975-5},
  langid = {english},
  file = {/Users/dkapitan/Zotero/storage/RFT7S6KP/Otto et al. - 2022 - Designing Data Spaces The Ecosystem Approach to C.pdf}
}

@article{ozalp2022digital,
  title = {``{{Digital Colonization}}'' of {{Highly Regulated Industries}}: {{An Analysis}} of {{Big Tech Platforms}}' {{Entry}} into {{Health Care}} and {{Education}}},
  shorttitle = {``{{Digital Colonization}}'' of {{Highly Regulated Industries}}},
  author = {Ozalp, Hakan and Ozcan, Pinar and Dinckol, Dize and Zachariadis, Markos and Gawer, Annabelle},
  year = {2022},
  month = aug,
  journal = {California Management Review},
  volume = {64},
  number = {4},
  pages = {78--107},
  publisher = {SAGE Publications Inc},
  issn = {0008-1256},
  doi = {10.1177/00081256221094307},
  urldate = {2023-02-16},
  abstract = {Digital platforms have disrupted many sectors but have not yet visibly transformed highly regulated industries. This study of Big Tech entry in healthcare and education explores how platforms have begun to enter highly regulated industries systematically and effectively. It presents a four-stage process model of platform entry, which we term as ?digital colonization.? This involves provision of data infrastructure services to regulated incumbents; data capture in the highly regulated industry; provision of data-driven insights; and design and commercialization of new products and services. The article clarifies platforms? sources of competitive advantage in highly regulated industries and concludes with managerial and policy recommendations.},
  langid = {english},
  file = {/Users/dkapitan/Zotero/storage/EQ9T3W96/Ozalp et al. - 2022 - “Digital Colonization” of Highly Regulated Industr.pdf}
}

@article{panda2016decentralization,
  title = {Decentralization and Health System Performance -- a Focused Review of Dimensions, Difficulties, and Derivatives in {{India}}},
  author = {Panda, Bhuputra and Thakur, Harshad P.},
  year = {2016},
  month = oct,
  journal = {BMC Health Services Research},
  volume = {16},
  number = {6},
  pages = {561},
  issn = {1472-6963},
  doi = {10.1186/s12913-016-1784-9},
  urldate = {2024-08-12},
  abstract = {One of the principal goals of any health care system is to improve health through the provision of clinical and public health services. Decentralization as a reform measure aims to improve inputs, management processes and health outcomes, and has political, administrative and financial connotations. It is argued that the robustness of a health system in achieving desirable outcomes is contingent upon the width and depth of `decision space' at the local level. Studies have used different approaches to examine one or more facets of decentralization and its effect on health system functioning; however, lack of consensus on an acceptable framework is a critical gap in determining its quantum and quality. Theorists have resorted to concepts of `trust', `convenience' and `mutual benefits' to explain, define and measure components of governance in health. In the emerging `continuum of health services' model, the challenge lies in identifying variables of performance (fiscal allocation, autonomy at local level, perception of key stakeholders, service delivery outputs, etc.) through the prism of decentralization in the first place, and in establishing directed relationships among them.},
  keywords = {Decentralization,Derivatives,Difficulties,Dimensions,Efficiency,Focused review,Health system performance,India,Odisha},
  file = {/Users/dkapitan/Zotero/storage/X6I7RR8L/Panda and Thakur - 2016 - Decentralization and health system performance – a focused review of dimensions, difficulties, and d.pdf;/Users/dkapitan/Zotero/storage/6DNMPL2K/s12913-016-1784-9.html}
}

@article{panturu2023potentiele,
  title = {Potenti{\"e}le Gamechanger Zorgverzekeringsmarkt},
  author = {Panturu, Andreea and Oskam, Michel and {van Vliet}, Rene and {van Kleef}, Richard},
  year = {2023},
  month = dec,
  journal = {Actuaris},
  issn = {0929-4562},
  abstract = {Naast de nominale, risico-onafhankelijke premies van hun verzekerden, ontvangen zorgverzekeraars jaarlijks een bijdrage uit het Zorgverzekeringsfonds. Deze zogenaamde `vereveningsbijdrage' is afhankelijk van de risicokenmerken van de verzekerden.}
}

@article{pedreira2023composable,
  title = {The {{Composable Data Management System Manifesto}}},
  author = {Pedreira, Pedro and Erling, Orri and Karanasos, Konstantinos and Schneider, Scott and McKinney, Wes and Valluri, Satya R and Zait, Mohamed and Nadeau, Jacques},
  year = {2023},
  month = jun,
  journal = {Proceedings of the VLDB Endowment},
  volume = {16},
  number = {10},
  pages = {2679--2685},
  issn = {2150-8097},
  doi = {10.14778/3603581.3603604},
  urldate = {2023-12-27},
  abstract = {The requirement for specialization in data management systems has evolved faster than our software development practices. After decades of organic growth, this situation has created a siloed landscape composed of hundreds of products developed and maintained as monoliths, with limited reuse between systems. This fragmentation has resulted in developers often reinventing the wheel, increased maintenance costs, and slowed down innovation. It has also affected the end users, who are often required to learn the idiosyncrasies of dozens of incompatible SQL and non-SQL API dialects, and settle for systems with incomplete functionality and inconsistent semantics. In this vision paper, considering the recent popularity of open source projects aimed at standardizing different aspects of the data stack, we advocate for a paradigm shift in how data management systems are designed. We believe that by decomposing these into a modular stack of reusable components, development can be streamlined while creating a more consistent experience for users. Towards that goal, we describe the state-ofthe-art, principal open source technologies, and highlight open questions and areas where additional research is needed. We hope this work will foster collaboration, motivate further research, and promote a more composable future for data management.},
  langid = {english},
  file = {/Users/dkapitan/Zotero/storage/SVVTZQSR/Pedreira et al. - 2023 - The Composable Data Management System Manifesto.pdf}
}

@article{pedrera-jimenez2023can,
  title = {Can {{OpenEHR}}, {{ISO}} 13606, and {{HL7 FHIR Work Together}}? {{An Agnostic Approach}} for the {{Selection}} and {{Application}} of {{Electronic Health Record Standards}} to the {{Next-Generation Health Data Spaces}}},
  shorttitle = {Can {{OpenEHR}}, {{ISO}} 13606, and {{HL7 FHIR Work Together}}?},
  author = {{Pedrera-Jim{\'e}nez}, Miguel and {Garc{\'i}a-Barrio}, Noelia and Frid, Santiago and Moner, David and {Bosc{\'a}-Tom{\'a}s}, Diego and {Lozano-Rub{\'i}}, Raimundo and Kalra, Dipak and Beale, Thomas and {Mu{\~n}oz-Carrero}, Adolfo and {Serrano-Balazote}, Pablo},
  year = {2023},
  month = dec,
  journal = {Journal of Medical Internet Research},
  volume = {25},
  number = {1},
  pages = {e48702},
  publisher = {JMIR Publications Inc., Toronto, Canada},
  doi = {10.2196/48702},
  urldate = {2024-01-16},
  abstract = {In order to maximize the value of electronic health records (EHRs) for both health care and secondary use, it is necessary for the data to be interoperable and reusable without loss of the original meaning and context, in accordance with the findable, accessible, interoperable, and reusable (FAIR) principles. To achieve this, it is essential for health data platforms to incorporate standards that facilitate addressing needs such as formal modeling of clinical knowledge (health domain concepts) as well as the harmonized persistence, query, and exchange of data across different information systems and organizations. However, the selection of these specifications has not been consistent across the different health data initiatives, often applying standards to address needs for which they were not originally designed. This issue is essential in the current scenario of implementing the European Health Data Space, which advocates harmonization, interoperability, and reuse of data without regulating the specific standards to be applied for this purpose. Therefore, this viewpoint aims to establish a coherent, agnostic, and homogeneous framework for the use of the most impactful EHR standards in the new-generation health data spaces: OpenEHR, International Organization for Standardization (ISO) 13606, and Health Level 7 (HL7) Fast Healthcare Interoperability Resources (FHIR). Thus, a panel of EHR standards experts has discussed several critical points to reach a consensus that will serve decision-making teams in health data platform projects who may not be experts in these EHR standards. It was concluded that these specifications possess different capabilities related to modeling, flexibility, and implementation resources. Because of this, in the design of future data platforms, these standards must be applied based on the specific needs they were designed for, being likewise fully compatible with their combined functional and technical implementation.},
  langid = {english},
  file = {/Users/dkapitan/Zotero/storage/KPLKECR6/Pedrera-Jiménez et al. - 2023 - Can OpenEHR, ISO 13606, and HL7 FHIR Work Together.pdf;/Users/dkapitan/Zotero/storage/SYN8B3VU/e48702.html}
}

@article{pfaff2019fast,
  title = {Fast {{Healthcare Interoperability Resources}} ({{FHIR}}) as a {{Meta Model}} to {{Integrate Common Data Models}}: {{Development}} of a {{Tool}} and {{Quantitative Validation Study}}},
  shorttitle = {Fast {{Healthcare Interoperability Resources}} ({{FHIR}}) as a {{Meta Model}} to {{Integrate Common Data Models}}},
  author = {Pfaff, Emily Rose and Champion, James and Bradford, Robert Louis and Clark, Marshall and Xu, Hao and Fecho, Karamarie and Krishnamurthy, Ashok and Cox, Steven and Chute, Christopher G. and Taylor, Casey Overby and Ahalt, Stan},
  year = {2019},
  month = oct,
  journal = {JMIR Medical Informatics},
  volume = {7},
  number = {4},
  pages = {e15199},
  publisher = {JMIR Publications Inc., Toronto, Canada},
  doi = {10.2196/15199},
  urldate = {2024-05-27},
  abstract = {Background: In a multisite clinical research collaboration, institutions may or may not use the same common data model (CDM) to store clinical data. To overcome this challenge, we proposed to use Health Level 7's Fast Healthcare Interoperability Resources (FHIR) as a meta-CDM---a single standard to represent clinical data. Objective: In this study, we aimed to create an open-source application termed the Clinical Asset Mapping Program for FHIR (CAMP FHIR) to efficiently transform clinical data to FHIR for supporting source-agnostic CDM-to-FHIR mapping. Methods: Mapping with CAMP FHIR involves (1) mapping each source variable to its corresponding FHIR element and (2) mapping each item in the source data's value sets to the corresponding FHIR value set item for variables with strict value sets. To date, CAMP FHIR has been used to transform 108 variables from the Informatics for Integrating Biology \&amp; the Bedside (i2b2) and Patient-Centered Outcomes Research Network data models to fields across 7 FHIR resources. It is designed to allow input from any source data model and will support additional FHIR resources in the future. Results: We have used CAMP FHIR to transform data on approximately 23,000 patients with asthma from our institution's i2b2 database. Data quality and integrity were validated against the origin point of the data, our enterprise clinical data warehouse. Conclusions: We believe that CAMP FHIR can serve as an alternative to implementing new CDMs on a project-by-project basis. Moreover, the use of FHIR as a CDM could support rare data sharing opportunities, such as collaborations between academic medical centers and community hospitals. We anticipate adoption and use of CAMP FHIR to foster sharing of clinical data across institutions for downstream applications in translational research.},
  copyright = {This is an open-access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work, first published JMIR Medical Informatics, is properly cited. The complete bibliographic information, a link to the original publication on https://medinform.jmir.org/, as well as this copyright and license information must be included.},
  langid = {english},
  file = {/Users/dkapitan/Zotero/storage/LLMCZ2WS/Pfaff et al. - 2019 - Fast Healthcare Interoperability Resources (FHIR) .pdf}
}

@article{pirmani2023journey,
  title = {The {{Journey}} of {{Data Within}} a {{Global Data Sharing Initiative}}: {{A Federated}} 3-{{Layer Data Analysis Pipeline}} to {{Scale Up Multiple Sclerosis Research}}},
  shorttitle = {The {{Journey}} of {{Data Within}} a {{Global Data Sharing Initiative}}},
  author = {Pirmani, Ashkan and Brouwer, Edward De and Geys, Lotte and Parciak, Tina and Moreau, Yves and Peeters, Liesbet M.},
  year = {2023},
  month = nov,
  journal = {JMIR Medical Informatics},
  volume = {11},
  number = {1},
  pages = {e48030},
  publisher = {JMIR Publications Inc., Toronto, Canada},
  doi = {10.2196/48030},
  urldate = {2024-05-27},
  abstract = {Background: Investigating low-prevalence diseases such as multiple sclerosis is challenging because of the rather small number of individuals affected by this disease and the scattering of real-world data across numerous data sources. These obstacles impair data integration, standardization, and analysis, which negatively impact the generation of significant meaningful clinical evidence. Objective: This study aims to present a comprehensive, research question--agnostic, multistakeholder-driven end-to-end data analysis pipeline that accommodates 3 prevalent data-sharing streams: individual data sharing, core data set sharing, and federated model sharing. Methods: A demand-driven methodology is employed for standardization, followed by 3 streams of data acquisition, a data quality enhancement process, a data integration procedure, and a concluding analysis stage to fulfill real-world data-sharing requirements. This pipeline's effectiveness was demonstrated through its successful implementation in the COVID-19 and multiple sclerosis global data sharing initiative. Results: The global data sharing initiative yielded multiple scientific publications and provided extensive worldwide guidance for the community with multiple sclerosis. The pipeline facilitated gathering pertinent data from various sources, accommodating distinct sharing streams and assimilating them into a unified data set for subsequent statistical analysis or secure data examination. This pipeline contributed to the assembly of the largest data set of people with multiple sclerosis infected with COVID-19. Conclusions: The proposed data analysis pipeline exemplifies the potential of global stakeholder collaboration and underlines the significance of evidence-based decision-making. It serves as a paradigm for how data sharing initiatives can propel advancements in health care, emphasizing its adaptability and capacity to address diverse research inquiries.},
  copyright = {This is an open-access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work, first published JMIR Medical Informatics, is properly cited. The complete bibliographic information, a link to the original publication on https://medinform.jmir.org/, as well as this copyright and license information must be included.},
  langid = {english},
  file = {/Users/dkapitan/Zotero/storage/3TF8G3SC/Pirmani et al. - 2023 - The Journey of Data Within a Global Data Sharing I.pdf}
}

@article{prainsack2019loggeda,
  title = {Logged out: {{Ownership}}, Exclusion and Public Value in the Digital Data and Information Commons},
  shorttitle = {Logged Out},
  author = {Prainsack, Barbara},
  year = {2019},
  month = jan,
  journal = {Big Data \& Society},
  volume = {6},
  number = {1},
  pages = {2053951719829773},
  publisher = {SAGE Publications Ltd},
  issn = {2053-9517},
  doi = {10.1177/2053951719829773},
  urldate = {2024-08-19},
  abstract = {In recent years, critical scholarship has drawn attention to increasing power differentials between corporations that use data and people whose data is used. A growing number of scholars see digital data and information commons as a way to counteract this asymmetry. In this paper I raise two concerns with this argument: First, because digital data and information can be in more than one place at once, governance models for physical common-pool resources cannot be easily transposed to digital commons. Second, not all data and information commons are suitable to address power differentials. In order to create digital commons that effectively address power asymmetries we must pay more systematic attention to the issue of exclusion from digital data and information commons. Why and how digital data and information commons exclude, and what the consequences of such exclusion are, decide whether commons can change power asymmetries or whether they are more likely to perpetuate them.},
  langid = {english},
  file = {/Users/dkapitan/Zotero/storage/4ILW5EWA/Prainsack - 2019 - Logged out Ownership, exclusion and public value .pdf}
}

@article{prainsack2022data,
  title = {Data Solidarity: A Blueprint for Governing Health Futures},
  shorttitle = {Data Solidarity},
  author = {Prainsack, Barbara and {El-Sayed}, Seliem and Forg{\'o}, Nikolaus and Szoszkiewicz, {\L}ukasz and Baumer, Philipp},
  year = {2022},
  month = nov,
  journal = {The Lancet Digital Health},
  volume = {4},
  number = {11},
  pages = {e773-e774},
  publisher = {Elsevier},
  issn = {2589-7500},
  doi = {10.1016/S2589-7500(22)00189-3},
  urldate = {2022-11-24},
  langid = {english},
  pmid = {36307191},
  file = {/Users/dkapitan/Zotero/storage/DRPB7AV3/Prainsack et al. - 2022 - Data solidarity a blueprint for governing health futures.pdf}
}

@article{prainsack2022why,
  title = {Why Paying Individual People for Their Health Data Is a Bad Idea},
  author = {Prainsack, Barbara and Forg{\'o}, Nikolaus},
  year = {2022},
  month = oct,
  journal = {Nature Medicine},
  volume = {28},
  number = {10},
  pages = {1989--1991},
  publisher = {Nature Publishing Group},
  issn = {1546-170X},
  doi = {10.1038/s41591-022-01955-4},
  urldate = {2024-08-27},
  abstract = {Paying individual people for their health data will widen inequalities and reduce altruism, luring people to sell their privacy. Health data should instead be treated as collective property, and commercial profits should be shared with the public.},
  copyright = {2022 Springer Nature America, Inc.},
  langid = {english},
  keywords = {Ethics,Law},
  file = {/Users/dkapitan/Zotero/storage/7US4KGGX/Prainsack and Forgó - 2022 - Why paying individual people for their health data.pdf}
}

@article{prainsack2023beyond,
  title = {Beyond {{Individual Rights}}: {{How Data Solidarity Gives People Meaningful Control}} over {{Data}}},
  shorttitle = {Beyond {{Individual Rights}}},
  author = {Prainsack, Barbara and {El-Sayed}, Seliem},
  year = {2023},
  month = nov,
  journal = {The American Journal of Bioethics},
  volume = {23},
  number = {11},
  pages = {36--39},
  issn = {1526-5161, 1536-0075},
  doi = {10.1080/15265161.2023.2256267},
  urldate = {2023-11-11},
  langid = {english},
  file = {/Users/dkapitan/Zotero/storage/T542DFXH/prainsack2023beyond.pdf}
}

@misc{projects,
  title = {Projects {\textbar} {{Digital Impact Exchange}}},
  urldate = {2024-08-20},
  abstract = {List of key projects provided by the Digital Impact Exchange, to support users in the deployment of digital technologies designed to address the Sustainable Development Goals (SDGs).},
  howpublished = {https://exchange.dial.global/projects/dominica-integrated-information-systems-for-health-diish},
  langid = {english},
  file = {/Users/dkapitan/Zotero/storage/TLPV6XQG/dominica-integrated-information-systems-for-health-diish.html}
}

@article{purnamajati2022data,
  title = {Data {{Access}}, {{Control}}, and {{Privacy Protection}} in the {{VODAN-Africa Architecture}}},
  author = {Purnama Jati, Putu Hadi and {van Reisen}, Mirjam and Flikkenschild, Erik and Oladipo, Fransisca and Meerman, Bert and Plug, Ruduan and Nodehi, Sara},
  year = {2022},
  month = oct,
  journal = {Data Intelligence},
  volume = {4},
  number = {4},
  pages = {938--954},
  issn = {2641-435X},
  doi = {10.1162/dint_a_00180},
  urldate = {2023-06-12},
  abstract = {The Virus Outbreak Data Network (VODAN)-Africa aims to contribute to the publication of Findable Accessible, Interoperable, and Reusable (FAIR) health data under well-defined access conditions. The next step in the VODAN-Africa architecture is to locally deploy the Center for Expanded Data Annotation and Retrieval (CEDAR) and arrange accessibility based on the `data visiting' concept. Locally curated and reposited machine-actionable data can be visited by queries or algorithms, provided that the conditions of access are met. The goal is to enable the multiple (re)use of data with secure access functionality by clinicians (patient care), an idea aligned with the FAIR-based Personal Health Train (PHT) concept. The privacy and security requirements in relation to the FAIR Data Host and the FAIRification workspace (to produce metadata) or dashboard (for the patient) must be clear to design the IT architecture. This article describes a (first) practice, a reference implementation in development, within the VODAN-Africa and Leiden University Medical Center community.},
  file = {/Users/dkapitan/Zotero/storage/DTQ8H42M/Purnama Jati et al. - 2022 - Data Access, Control, and Privacy Protection in th.pdf;/Users/dkapitan/Zotero/storage/XHXP43JL/Data-Access-Control-and-Privacy-Protection-in-the.html}
}

@article{purtova2023data,
  title = {Data as an Economic Good, Data as a Commons, and Data Governance},
  author = {Purtova, Nadya and {van Maanen}, Gijs},
  year = {2023},
  journal = {Law, Innovation and Technology},
  volume = {0},
  number = {0},
  pages = {1--42},
  publisher = {Routledge},
  issn = {1757-9961},
  doi = {10.1080/17579961.2023.2265270},
  urldate = {2024-02-05},
  abstract = {This paper provides a systematic and critical review of the economics literature on data as an economic good and draws lessons for data governance. We conclude that focusing on data as an economic good in governance efforts is hardwired to only result in more data production and cannot deliver other societal goals contrary to what is often claimed in the literature and policy. Data governance is often a red herring which distracts from other digital problems. The governance of digital society cannot rely exclusively on data-centric economic models. We review the literatures and the underlying empirical and political claims concerning data commons. While commons thinking is useful to frame digital problems in terms of ecologies, it has important limitations. We propose a political-ecological approach to governing the digital society, defined by ecological thinking about governance problems and the awareness of the political nature of framing the problems and mapping their ecological makeup.},
  keywords = {data as a resource,data commons,Data economy,data governance,data sharing,digital commons},
  file = {/Users/dkapitan/Zotero/storage/ASG6EB6V/Purtova and van Maanen - 2023 - Data as an economic good, data as a commons, and d.pdf}
}

@article{rajit2024tools,
  title = {Tools and Frameworks for Evaluating the Implementation of Learning Health Systems: A Scoping Review},
  shorttitle = {Tools and Frameworks for Evaluating the Implementation of Learning Health Systems},
  author = {Rajit, Darren and Reeder, Sandra and Johnson, Alison and Enticott, Joanne and Teede, Helena},
  year = {2024},
  month = aug,
  journal = {Health Research Policy and Systems},
  volume = {22},
  number = {1},
  pages = {95},
  issn = {1478-4505},
  doi = {10.1186/s12961-024-01179-7},
  urldate = {2024-09-06},
  abstract = {Despite increased interest in learning health systems (LHS), a paucity of guidance and tools for evaluating LHS implementation exists. To address this, we aim to undertake a scoping review on existing tools and evaluation of exemplars of LHS implementation.},
  langid = {english},
  keywords = {Artificial Intelligence,Evaluation,Healthcare improvement,Implementation science,Learning health systems},
  file = {/Users/dkapitan/Zotero/storage/MRC44LML/Rajit et al. - 2024 - Tools and frameworks for evaluating the implementa.pdf}
}

@article{raso2024anonymization,
  title = {Anonymization and {{Pseudonymization}} of {{FHIR Resources}} for {{Secondary Use}} of {{Healthcare Data}}},
  author = {Raso, Emanuele and Loreti, Pierpaolo and Ravaziol, Michele and Bracciale, Lorenzo},
  year = {2024},
  journal = {IEEE Access},
  volume = {12},
  pages = {44929--44939},
  issn = {2169-3536},
  doi = {10.1109/ACCESS.2024.3381034},
  urldate = {2024-04-15},
  abstract = {Along with the creation of medical profiles of patients, Electronic Health Records have several secondary missions, such as health economy and research. The recent, increasing adoption of a common standard, i.e., the Fast Healthcare Interoperability Resources (FHIR), makes it easier to exchange medical data among the several parties involved, for example, in an epidemiological research activity. However, this exchange process is hindered by regulatory frameworks due to privacy issues related to the presence of personal information, which allows patients to be identified directly (or indirectly) from their medical data. When properly used, de-identification techniques can provide crucial support in overcoming these problems. FHIR-DIET aims to bring flexibility and concreteness to the implementation of de-identification of health data, supporting many customised data-processing behaviours that can be easily configured and tailored to match specific use case requirements. Our solution enables faster and easier cooperation between legal and IT professionals to establish and implement de-identification rules. The performance evaluation demonstrates the viability of processing hundreds of FHIR patient information data per second using standard hardware. We believe FHIR-DIET can be a valuable tool to satisfy the current regulation requirements and help to create added-value for the secondary use of healthcare data.},
  copyright = {https://creativecommons.org/licenses/by-nc-nd/4.0/},
  langid = {english},
  file = {/Users/dkapitan/Zotero/storage/P9ZQ5ZEY/Raso et al. - 2024 - Anonymization and Pseudonymization of FHIR Resourc.pdf}
}

@misc{reflexive,
  title = {A {{Reflexive Account}} of {{Reusing Qualitative Data}}: {{Beyond Primary}}/{{Secondary Dualism}} - {{Libby Bishop}}, 2007},
  urldate = {2024-05-17},
  howpublished = {https://journals-sagepub-com.dianus.libr.tue.nl/doi/full/10.5153/sro.1553?casa\_token=PWhfY4sonZoAAAAA\%3A14bTcX9n0WmvAjOEnOsmedIpXVVvlLKnmVOD0d5iJJOfBJ-nRrDumAnlOVBx4H\_EJrsyZA3SfXTn},
  file = {/Users/dkapitan/Zotero/storage/D7CSA9QT/sro.html}
}

@article{reynolds2011open,
  title = {Open {{Source}}, {{Open Standards}}, and {{Health Care Information Systems}}},
  author = {Reynolds, Carl J. and Wyatt, Jeremy C.},
  year = {2011},
  month = feb,
  journal = {Journal of Medical Internet Research},
  volume = {13},
  number = {1},
  pages = {e1521},
  publisher = {JMIR Publications Inc., Toronto, Canada},
  doi = {10.2196/jmir.1521},
  urldate = {2024-05-29},
  abstract = {Recognition of the improvements in patient safety, quality of patient care, and efficiency that health care information systems have the potential to bring has led to significant investment. Globally the sale of health care information systems now represents a multibillion dollar industry. As policy makers, health care professionals, and patients, we have a responsibility to maximize the return on this investment. To this end we analyze alternative licensing and software development models, as well as the role of standards. We describe how licensing affects development. We argue for the superiority of open source licensing to promote safer, more effective health care information systems. We claim that open source licensing in health care information systems is essential to rational procurement strategy.},
  langid = {english},
  file = {/Users/dkapitan/Zotero/storage/NPY3U838/Reynolds and Wyatt - 2011 - Open Source, Open Standards, and Health Care Infor.pdf}
}

@article{rieke2020future,
  title = {The Future of Digital Health with Federated Learning},
  author = {Rieke, Nicola and Hancox, Jonny and Li, Wenqi and Milletar{\`i}, Fausto and Roth, Holger R. and Albarqouni, Shadi and Bakas, Spyridon and Galtier, Mathieu N. and Landman, Bennett A. and {Maier-Hein}, Klaus and Ourselin, S{\'e}bastien and Sheller, Micah and Summers, Ronald M. and Trask, Andrew and Xu, Daguang and Baust, Maximilian and Cardoso, M. Jorge},
  year = {2020},
  month = sep,
  journal = {npj Digital Medicine},
  volume = {3},
  number = {1},
  pages = {1--7},
  publisher = {Nature Publishing Group},
  issn = {2398-6352},
  doi = {10.1038/s41746-020-00323-1},
  urldate = {2023-04-23},
  abstract = {Data-driven machine learning (ML) has emerged as a promising approach for building accurate and robust statistical models from medical data, which is collected in huge volumes by modern healthcare systems. Existing medical data is not fully exploited by ML primarily because it sits in data silos and privacy concerns restrict access to this data. However, without access to sufficient data, ML will be prevented from reaching its full potential and, ultimately, from making the transition from research to clinical practice. This paper considers key factors contributing to this issue, explores how federated learning (FL) may provide a solution for the future of digital health and highlights the challenges and considerations that need to be addressed.},
  copyright = {2020 The Author(s)},
  langid = {english},
  keywords = {Medical imaging,Medical research},
  file = {/Users/dkapitan/Zotero/storage/DJI9BHQP/Rieke et al. - 2020 - The future of digital health with federated learni.pdf}
}

@article{rinaldi2021openehr,
  title = {From {{OpenEHR}} to {{FHIR}} and {{OMOP Data Model}} for {{Microbiology Findings}}},
  author = {Rinaldi, Eugenia and Thun, Sylvia},
  year = {2021},
  month = may,
  journal = {Studies in Health Technology and Informatics},
  volume = {281},
  pages = {402--406},
  issn = {1879-8365},
  doi = {10.3233/SHTI210189},
  abstract = {HiGHmed is a German Consortium where eight University Hospitals have agreed to the cross-institutional data exchange through novel medical informatics solutions. The HiGHmed Use Case Infection Control group has modelled a set of infection-related data in the openEHR format. In order to establish interoperability with the other German Consortia belonging to the same national initiative, we mapped the openEHR information to the Fast Healthcare Interoperability Resources (FHIR) format recommended within the initiative. FHIR enables fast exchange of data thanks to the discrete and independent data elements into which information is organized. Furthermore, to explore the possibility of maximizing analysis capabilities for our data set, we subsequently mapped the FHIR elements to the Observational Medical Outcomes Partnership Common Data Model (OMOP CDM). The OMOP data model is designed to support the conduct of research to identify and evaluate associations between interventions and outcomes caused by these interventions. Mapping across standard allows to exploit their peculiarities while establishing and/or maintaining interoperability. This article provides an overview of our experience in mapping infection control related data across three different standards openEHR, FHIR and OMOP CDM.},
  langid = {english},
  pmid = {34042774},
  keywords = {data model,Electronic Health Records,FHIR,Hospitals University,Humans,interoperability,mapping,Medical Informatics,microbiology,OMOP CDM,openEHR,standard},
  file = {/Users/dkapitan/Zotero/storage/TBIQUHPR/Rinaldi and Thun - 2021 - From OpenEHR to FHIR and OMOP Data Model for Micro.pdf}
}

@article{rochet2003platform,
  title = {Platform {{Competition}} in {{Two-sided Markets}}},
  author = {Rochet, Jean-Charles and Tirole, Jean},
  year = {2003},
  journal = {Journal of the European Economic Association},
  volume = {1},
  number = {4},
  eprint = {40005175},
  eprinttype = {jstor},
  pages = {990--1029},
  publisher = {Oxford University Press},
  issn = {1542-4766},
  urldate = {2024-04-23},
  abstract = {Many if not most markets with network externalities are two-sided. To succeed, platforms in industries such as software, portals and media, payment systems and the Internet, must "get both sides of the market on board." Accordingly, platforms devote much attention to their business model, that is, to how they court each side while making money overall. This paper builds a model of platform competition with two-sided markets. It unveils the determinants of price allocation and end-user surplus for different governance structures (profit-maximizing platforms and not-for-profit joint undertakings), and compares the outcomes with those under an integrated monopolist and a Ramsey planner.}
}

@article{rosenau2024uncovering,
  title = {Uncovering {{Harmonization Potential}} in {{Health Care Data Through Iterative Refinement}} of {{Fast Healthcare Interoperability Resources Profiles Based}} on {{Retrospective Discrepancy Analysis}}: {{Case Study}}},
  shorttitle = {Uncovering {{Harmonization Potential}} in {{Health Care Data Through Iterative Refinement}} of {{Fast Healthcare Interoperability Resources Profiles Based}} on {{Retrospective Discrepancy Analysis}}},
  author = {Rosenau, Lorenz and Behrend, Paul and Wiedekopf, Joshua and Gruendner, Julian and Ingenerf, Josef},
  year = {2024},
  month = jul,
  journal = {JMIR Medical Informatics},
  volume = {12},
  pages = {e57005},
  issn = {2291-9694},
  doi = {10.2196/57005},
  urldate = {2024-08-12},
  abstract = {Background: Cross-institutional interoperability between health care providers remains a recurring challenge worldwide. The German Medical Informatics Initiative, a collaboration of 37 university hospitals in Germany, aims to enable interoperability between partner sites by defining Fast Healthcare Interoperability Resources (FHIR) profiles for the cross-institutional exchange of health care data, the Core Data Set (CDS). The current CDS and its extension modules define elements representing patients' health care records. All university hospitals in Germany have made significant progress in providing routine data in a standardized format based on the CDS. In addition, the central research platform for health, the German Portal for Medical Research Data feasibility tool, allows medical researchers to query the available CDS data items across many participating hospitals. Objective: In this study, we aimed to evaluate a novel approach of combining the current top-down generated FHIR profiles with the bottom-up generated knowledge gained by the analysis of respective instance data. This allowed us to derive options for iteratively refining FHIR profiles using the information obtained from a discrepancy analysis. Methods: We developed an FHIR validation pipeline and opted to derive more restrictive profiles from the original CDS profiles. This decision was driven by the need to align more closely with the specific assumptions and requirements of the central feasibility platform's search ontology. While the original CDS profiles offer a generic framework adaptable for a broad spectrum of medical informatics use cases, they lack the specificity to model the nuanced criteria essential for medical researchers. A key example of this is the necessity to represent specific laboratory codings and values interdependencies accurately. The validation results allow us to identify discrepancies between the instance data at the clinical sites and the profiles specified by the feasibility platform and addressed in the future. Results: A total of 20 university hospitals participated in this study. Historical factors, lack of harmonization, a wide range of source systems, and case sensitivity of coding are some of the causes for the discrepancies identified. While in our case study, Conditions, Procedures, and Medications have a high degree of uniformity in the coding of instance data due to legislative requirements for billing in Germany, we found that laboratory values pose a significant data harmonization challenge due to their interdependency between coding and value. Conclusions: While the CDS achieves interoperability, different challenges for federated data access arise, requiring more specificity in the profiles to make assumptions on the instance data. We further argue that further harmonization of the instance data can significantly lower required retrospective harmonization efforts. We recognize that discrepancies cannot be resolved},
  langid = {english},
  file = {/Users/dkapitan/Zotero/storage/JVB7L4HM/Rosenau et al. - 2024 - Uncovering Harmonization Potential in Health Care Data Through Iterative Refinement of Fast Healthca.pdf}
}

@misc{rubegni2024designing,
  title = {Designing for {{Complementarity}}: {{A Conceptual Framework}} to {{Go Beyond}} the {{Current Paradigm}} of {{Using XAI}} in {{Healthcare}}},
  shorttitle = {Designing for {{Complementarity}}},
  author = {Rubegni, Elisa and Ayoub, Omran and Rizzo, Stefania Maria Rita and Barbero, Marco and Bernegger, Guenda and Faraci, Francesca and Mangili, Francesca and Soldini, Emiliano and Trimboli, Pierpaolo and Facchini, Alessandro},
  year = {2024},
  month = apr,
  number = {arXiv:2404.04638},
  eprint = {2404.04638},
  primaryclass = {cs},
  publisher = {arXiv},
  doi = {10.48550/arXiv.2404.04638},
  urldate = {2024-04-25},
  abstract = {The widespread use of Artificial Intelligence-based tools in the healthcare sector raises many ethical and legal problems, one of the main reasons being their black-box nature and therefore the seemingly opacity and inscrutability of their characteristics and decision-making process. Literature extensively discusses how this can lead to phenomena of over-reliance and under-reliance, ultimately limiting the adoption of AI. We addressed these issues by building a theoretical framework based on three concepts: Feature Importance, Counterexample Explanations, and Similar-Case Explanations. Grounded in the literature, the model was deployed within a case study in which, using a participatory design approach, we designed and developed a high-fidelity prototype. Through the co-design and development of the prototype and the underlying model, we advanced the knowledge on how to design AI-based systems for enabling complementarity in the decision-making process in the healthcare domain. Our work aims at contributing to the current discourse on designing AI systems to support clinicians' decision-making processes.},
  archiveprefix = {arXiv},
  keywords = {Computer Science - Human-Computer Interaction},
  file = {/Users/dkapitan/Zotero/storage/6RB8ZZB2/Rubegni et al. - 2024 - Designing for Complementarity A Conceptual Framew.pdf;/Users/dkapitan/Zotero/storage/KBYXZU98/2404.html}
}

@article{s.oliveira2019investigations,
  title = {Investigations into {{Data Ecosystems}}: A Systematic Mapping Study},
  shorttitle = {Investigations into {{Data Ecosystems}}},
  author = {S.~Oliveira, Marcelo Iury and Barros~Lima, Gl{\'o}ria De F{\'a}tima and Farias~L{\'o}scio, Bernadette},
  year = {2019},
  month = nov,
  journal = {Knowledge and Information Systems},
  volume = {61},
  number = {2},
  pages = {589--630},
  issn = {0219-1377, 0219-3116},
  doi = {10.1007/s10115-018-1323-6},
  urldate = {2024-08-12},
  abstract = {Data Ecosystems are socio-technical complex networks in which actors interact and collaborate with each other to find, archive, publish, consume, or reuse data as well as to foster innovation, create value, and support new businesses. While the Data Ecosystem field is thus arguably gaining in importance, research on this subject is still in its early stages of development. Up until now, not many academic papers related to Data Ecosystems have been published. Furthermore, to the best of our knowledge, there has been no systematic review of the literature on Data Ecosystems. In this study, we provide an overview of the current literature on Data Ecosystems by conducting a systematic mapping study. This study is intended to function as a snapshot of the research in the field and by doing so identifies the different definitions of Data Ecosystem and analyzes the evolution of Data Ecosystem research. The studies selected have been classified into categories related to the study method, contribution, research topic, and ecosystem domains. Finally, we analyze how Data Ecosystems are structured and organized, and what benefits can be expected from Data Ecosystems and what their limitations are.},
  langid = {english},
  file = {/Users/dkapitan/Zotero/storage/GXPUE73K/S. Oliveira et al. - 2019 - Investigations into Data Ecosystems a systematic mapping study.pdf}
}

@article{sachs2019six,
  title = {Six {{Transformations}} to Achieve the {{Sustainable Development Goals}}},
  author = {Sachs, Jeffrey D. and {Schmidt-Traub}, Guido and Mazzucato, Mariana and Messner, Dirk and Nakicenovic, Nebojsa and Rockstr{\"o}m, Johan},
  year = {2019},
  month = aug,
  journal = {Nature Sustainability},
  volume = {2},
  number = {9},
  pages = {805--814},
  issn = {2398-9629},
  doi = {10.1038/s41893-019-0352-9},
  urldate = {2023-12-12},
  langid = {english},
  file = {/Users/dkapitan/Zotero/storage/SPBF3YQL/Sachs et al. - 2019 - Six Transformations to achieve the Sustainable Dev.pdf}
}

@article{sanctis2022maintaining,
  title = {Maintaining {{Continuity}} of {{Care}} for {{Expectant Mothers}} in {{Kenya During}} the {{COVID-19 Pandemic}}: {{A Study}} of {{MomCare}}},
  shorttitle = {Maintaining {{Continuity}} of {{Care}} for {{Expectant Mothers}} in {{Kenya During}} the {{COVID-19 Pandemic}}},
  author = {Sanctis, Teresa De and Etiebet, Mary-Ann and Janssens, Wendy and van der Graaf, Mark H. and van Montfort, Colette and Waiyaiya, Emma and Spieker, Nicole},
  year = {2022},
  month = aug,
  journal = {Global Health: Science and Practice},
  volume = {10},
  number = {4},
  issn = {2169-575X},
  doi = {10.9745/GHSP-D-21-00665},
  urldate = {2023-02-03},
  abstract = {In Kenya, early coronavirus disease (COVID-19) modeling studies predicted that disruptions in antenatal care and hospital services could increase indirect maternal and neonatal deaths and stillbirths. As the Kenyan government enforced lockdowns and a curfew, many mothers-to-be were unable to safely reach hospital facilities, especially at night. Fear of contracting COVID-19, increasing costs of accessing care, stigma, and falling incomes forced many expectant mothers to give birth at home. MomCare, which primarily serves communities in remote areas and urban slums, links mothers-to-be with payers and health care providers, following a standardized pregnancy program based on World Health Organization guidelines at a predetermined cost and quality. Expectant mothers gain access to care through a mobile wallet on their feature phone (voice, text, and basic internet), and providers are paid after appropriate care is given. Within the first 3 weeks of the pandemic in Kenya, the following services were added to the MomCare bundle: emergency ambulance services during curfew hours, extended bed allowances to encourage early care, phone calls to check on mothers approaching their delivery dates and to promote the generation of a birth plan, SMS messages to inform mothers of open facilities and COVID-19 protocols, and training for clinic staff in managing COVID-19 patients and infection prevention. We compare data collected through the MomCare platform during the 6 months before the first confirmed COVID-19 case in Kenya (September 2019--February 2020) with data collected during the 6 months that followed. This study shows that care-seeking behaviors (enrollment, antenatal/postnatal care, skilled deliveries) increased for mothers-to-be enrolled in MomCare during the COVID-19 lockdowns, while quality of care and outcomes were maintained. Public health practitioners can promote interactive, patient-driven technology like MomCare to augment traditional responses, quickly linking payments with patients and providers in times of crisis.},
  copyright = {{\copyright} De Sanctis et al.. This is an open-access article distributed under the terms of the Creative Commons Attribution 4.0 International License (CC BY 4.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are properly cited. To view a copy of the license, visit https://creativecommons.org/licenses/by/4.0/. When linking to this article, please use the following permanent link: https://doi.org/10.9745/GHSP-D-21-00665},
  langid = {english},
  file = {/Users/dkapitan/Zotero/storage/BKALR7T7/Sanctis et al. - 2022 - Maintaining Continuity of Care for Expectant Mothe.pdf}
}

@article{scheibner2021revolutionizing,
  title = {Revolutionizing {{Medical Data Sharing Using Advanced Privacy-Enhancing Technologies}}: {{Technical}}, {{Legal}}, and {{Ethical Synthesis}}},
  shorttitle = {Revolutionizing {{Medical Data Sharing Using Advanced Privacy-Enhancing Technologies}}},
  author = {Scheibner, James and Raisaro, Jean Louis and {Troncoso-Pastoriza}, Juan Ram{\'o}n and Ienca, Marcello and Fellay, Jacques and Vayena, Effy and Hubaux, Jean-Pierre},
  year = {2021},
  month = feb,
  journal = {Journal of Medical Internet Research},
  volume = {23},
  number = {2},
  pages = {e25120},
  publisher = {JMIR Publications Inc., Toronto, Canada},
  doi = {10.2196/25120},
  urldate = {2024-02-05},
  abstract = {Multisite medical data sharing is critical in modern clinical practice and medical research. The challenge is to conduct data sharing that preserves individual privacy and data utility. The shortcomings of traditional privacy-enhancing technologies mean that institutions rely upon bespoke data sharing contracts. The lengthy process and administration induced by these contracts increases the inefficiency of data sharing and may disincentivize important clinical treatment and medical research.  This paper provides a synthesis between 2 novel advanced privacy-enhancing technologies---homomorphic encryption and secure multiparty computation (defined together as multiparty homomorphic encryption). These privacy-enhancing technologies provide a mathematical guarantee of privacy, with multiparty homomorphic encryption providing a performance advantage over separately using homomorphic encryption or secure multiparty computation. We argue multiparty homomorphic encryption fulfills legal requirements for medical data sharing under the European Union's General Data Protection Regulation which has set a global benchmark for data protection. Specifically, the data processed and shared using multiparty homomorphic encryption can be considered anonymized data. We explain how multiparty homomorphic encryption can reduce the reliance upon customized contractual measures between institutions. The proposed approach can accelerate the pace of medical research while offering additional incentives for health care and research institutes to employ common data interoperability standards.},
  langid = {english},
  file = {/Users/dkapitan/Zotero/storage/TDJ64DAV/Scheibner et al. - 2021 - Revolutionizing Medical Data Sharing Using Advance.pdf;/Users/dkapitan/Zotero/storage/QNV7X8TJ/e25120.html}
}

@phdthesis{schlatt2022whole,
  type = {Doctoral Thesis},
  title = {The {{Whole Is More Than}} the {{Sum}} of {{Its Parts}} : {{On}} the {{Design}} of {{Decentralized Information Systems}}},
  shorttitle = {The {{Whole Is More Than}} the {{Sum}} of {{Its Parts}}},
  author = {Schlatt, Vincent},
  year = {2022},
  address = {Bayreuth},
  doi = {10.15495/EPub_UBT_00006428},
  urldate = {2024-08-12},
  langid = {english},
  school = {Universit{\"a}t Bayreuth, Rechts- und Wirtschaftswissenschaftliche Fakult{\"a}t},
  file = {/Users/dkapitan/Zotero/storage/SZ8ZIJ67/70369.html}
}

@article{schultes2023fair,
  title = {The {{FAIR}} Hourglass: {{A}} Framework for {{FAIR}} Implementation},
  shorttitle = {The {{FAIR}} Hourglass},
  author = {Schultes, Erik},
  editor = {Magagna, Barbara},
  year = {2023},
  month = jan,
  journal = {FAIR Connect},
  volume = {1},
  number = {1},
  pages = {13--17},
  issn = {2949799X},
  doi = {10.3233/FC-221514},
  urldate = {2023-04-04},
  abstract = {The FAIR Hourglass provides a framework to organize two general phases of FAIR implementation: FAIRification (top) and FAIR Orchestration (bottom). The center of the hourglass represents the use of widely agreed-upon open, minimal standards ensuring machine-actionability.},
  langid = {english},
  file = {/Users/dkapitan/Zotero/storage/C79VBWCR/Schultes - 2023 - The FAIR hourglass A framework for FAIR implement.pdf}
}

@article{sein2011action,
  title = {Action {{Design Research}}},
  author = {Sein, Maung and Henfridsson, Ola and Purao, Sandeep and Rossi, Matti and Lindgren, Rikard},
  year = {2011},
  month = mar,
  journal = {MIS Quarterly},
  volume = {35},
  pages = {37--56},
  doi = {10.2307/23043488},
  abstract = {Design research (DR) positions information technology artifacts at the core of the Information Systems discipline. However, dominant DR thinking takes a technological view of the IT artifact, paying scant attention to its shaping by the organizational context. Consequently, existing DR methods focus on building the artifact and relegate evaluation to a subsequent and separate phase. They value technological rigor at the cost of organizational relevance, and fail to recognize that the artifact emerges from interaction with the organizational context even when its initial design is guided by the researchers' intent. We propose action design research (ADR) as a new DR method to address this problem. ADR reflects the premise that IT artifacts are ensembles shaped by the organizational context during development and use. The method conceptualizes the research process as containing the inseparable and inherently interwoven activities of building the IT artifact, intervening in the organization, and evaluating it concurrently. The essay describes the stages of ADR and associated principles that encapsulate its underlying beliefs and values. We illustrate ADR through a case of competence management at Volvo IT.},
  file = {/Users/dkapitan/Zotero/storage/9TW5LM9F/Sein et al. - 2011 - Action Design Research.pdf}
}

@misc{selforganization,
  title = {Self-{{Organization}} and {{Resilience}} for {{Networked Systems}}: {{Design Principles}} and {{Open Research Issues}} {\textbar} {{IEEE Journals}} \& {{Magazine}} {\textbar} {{IEEE Xplore}}},
  urldate = {2024-04-28},
  howpublished = {https://ieeexplore-ieee-org.dianus.libr.tue.nl/abstract/document/8645632?casa\_token=cmxSVwavipcAAAAA:ELDWFCKprHVtS5OWxyT9PhYUpld5ashU69pBr5LGG\_UObnSfiIzFq288TUHjH2STWz231maA},
  file = {/Users/dkapitan/Zotero/storage/DDPS9X9S/Self-Organization and Resilience for Networked Sys.pdf}
}

@article{seward2021guide,
  title = {A Guide to Systems-Level, Participatory, Theory-Informed Implementation Research in Global Health},
  author = {Seward, Nadine and Hanlon, Charlotte and {Hinrichs-Kraples}, Saba and Lund, Crick and Murdoch, Jamie and Taylor Salisbury, Tatiana and Verhey, Ruth and Shidhaye, Rahul and Thornicroft, Graham and Araya, Ricardo and Sevdalis, Nick},
  year = {2021},
  month = dec,
  journal = {BMJ Global Health},
  volume = {6},
  number = {12},
  pages = {e005365},
  issn = {2059-7908},
  doi = {10.1136/bmjgh-2021-005365},
  urldate = {2024-08-12},
  abstract = {Implementation research is a multidisciplinary field that addresses the complex phenomenon of how context influences our ability to deliver evidenceinformed healthcare. There is increasing realisation of the importance of applying robust implementation research to scale-up life-saving interventions that meet health-related sustainable development goals. However, the lack of high-quality implementation research is impeding our ability to meet these targets, globally. Within implementation research, theory refers to the proposed hypothesis and/or explanation of how an intervention is expected to interact with the local context and actors to bring about change. Although there is increasing interest in applying theory to understand how and why implementation programmes work in real-world settings, global health actors still tend to favour impact evaluations conducted in controlled environments. This may, in part, be due to the relative novelty as well as methodological complexity of implementation research and the need to draw on divergent disciplines, including epidemiology, implementation science and social sciences. Because of this, implementation research is faced with a particular set of challenges about how to reconcile different ways of thinking and constructing knowledge about healthcare interventions. To help translate some of the ambiguity surrounding how divergent theoretical approaches and methods contribute to implementation research, we draw on our multidisciplinary expertise in the field, particularly in global health. We offer an overview of the different theoretical approaches and describe how they are applied to continuously select, monitor and evaluate implementation strategies throughout the different phases of implementation research. In doing so, we offer a relatively brief, user-focused guide to help global health actors implement and report on evaluation of evidencebased and scalable interventions, programmes and practices.},
  langid = {english},
  file = {/Users/dkapitan/Zotero/storage/68DEN38K/Seward et al. - 2021 - A guide to systems-level, participatory, theory-informed implementation research in global health.pdf}
}

@article{shabani2022will,
  title = {Will the {{European Health Data Space}} Change Data Sharing Rules?},
  author = {Shabani, Mahsa},
  year = {2022},
  month = mar,
  journal = {Science},
  volume = {375},
  number = {6587},
  pages = {1357--1359},
  publisher = {American Association for the Advancement of Science},
  doi = {10.1126/science.abn4874},
  urldate = {2024-08-13},
  file = {/Users/dkapitan/Zotero/storage/4N83FKMU/Shabani - 2022 - Will the European Health Data Space change data sh.pdf}
}

@article{sharon2018when,
  title = {When Digital Health Meets Digital Capitalism, How Many Common Goods Are at Stake?},
  author = {Sharon, Tamar},
  year = {2018},
  month = jul,
  journal = {Big Data \& Society},
  volume = {5},
  number = {2},
  pages = {2053951718819032},
  publisher = {SAGE Publications Ltd},
  issn = {2053-9517},
  doi = {10.1177/2053951718819032},
  abstract = {In recent years, all major consumer technology corporations have moved into the domain of health research. This `Googlization of health research' (`GHR') begs the question of how the common good will be served in this research. As critical data scholars contend, such phenomena must be situated within the political economy of digital capitalism in order to foreground the question of public interest and the common good. Here, trends like GHR are framed within a double, incommensurable logic, where private gain and economic value are pitted against public good and societal value. While helpful for highlighting the exploitative potential of digital capitalism, this framing is limiting, insofar as it acknowledges only one conception of the common good. This article uses the analytical framework of modes of justification developed by Boltanksi and Th{\'e}venot to identify a plurality of orders of worth and conceptualizations of the common good at work in GHR. Not just the `civic' (doing good for society) and `market' (enhancing wealth creation) orders, but also an `industrial' (increasing efficiency), a `project' (innovation and experimentation), and what I call a `vitalist' (proliferating life) order. Using promotional material of GHR initiatives and preliminary interviews with participants in GHR projects, I ask what moral orientations guide different actors in GHR. Engaging seriously with these different conceptions of the common good is paramount. First, in order to critically evaluate them and explicate what is at stake in the move towards GHR, and ultimately, in order to develop viable governance solutions that ensure strong `civic' components.},
  langid = {english},
  keywords = {common good,digital capitalism,Digital health,Googlization of health research,moral repertoires,public values},
  file = {/Users/dkapitan/Zotero/storage/WTWHWGVC/Sharon - 2018 - When digital health meets digital capitalism, how .pdf}
}

@article{shija2021access,
  title = {Access to {{Essential Maternal Health Commodities Key}} to {{Improving Quality}} and {{Adherence}} to {{Maternal Healthcare Regimes}}: {{Experience}} from a {{MomCare Project}} in {{Northern Tanzania}}},
  shorttitle = {Access to {{Essential Maternal Health Commodities Key}} to {{Improving Quality}} and {{Adherence}} to {{Maternal Healthcare Regimes}}},
  author = {Shija, Liberatha and Yokoyana, Johnson and Mrema, Anunsiatha and Bwakea, Jonia and Kiwale, Theodora and Massawe, Neema},
  year = {2021},
  month = jul,
  journal = {AIJR Abstracts},
  publisher = {AIJR Publisher},
  urldate = {2023-02-02},
  langid = {american},
  file = {/Users/dkapitan/Zotero/storage/MITWIRCG/Shija et al. - 2021 - Access to Essential Maternal Health Commodities Ke.pdf;/Users/dkapitan/Zotero/storage/HFVGCG9P/1205.html}
}

@article{sigvartsenimplementation,
  title = {Implementation Guide for {{Norwegian}} Usage of {{IHE XDS}}, {{XCA}} and {{XUA}}},
  author = {Sigvartsen, Roy},
  langid = {english},
  file = {/Users/dkapitan/Zotero/storage/FELZ7XJL/Sigvartsen - Implementation guide for Norwegian usage of IHE XD.pdf}
}

@article{sinaci2023data,
  title = {A {{Data Transformation Methodology}} to {{Create Findable}}, {{Accessible}}, {{Interoperable}}, and {{Reusable Health Data}}: {{Software Design}}, {{Development}}, and {{Evaluation Study}}},
  shorttitle = {A {{Data Transformation Methodology}} to {{Create Findable}}, {{Accessible}}, {{Interoperable}}, and {{Reusable Health Data}}},
  author = {Sinaci, A Anil and Gencturk, Mert and Teoman, Huseyin Alper and Laleci Erturkmen, Gokce Banu and {Alvarez-Romero}, Celia and {Martinez-Garcia}, Alicia and {Poblador-Plou}, Beatriz and {Carmona-P{\'i}rez}, Jon{\'a}s and L{\"o}be, Matthias and {Parra-Calderon}, Carlos Luis},
  year = {2023},
  month = mar,
  journal = {Journal of Medical Internet Research},
  volume = {25},
  pages = {e42822},
  issn = {1439-4456},
  doi = {10.2196/42822},
  urldate = {2023-07-05},
  abstract = {Background Sharing health data is challenging because of several technical, ethical, and regulatory issues. The Findable, Accessible, Interoperable, and Reusable (FAIR) guiding principles have been conceptualized to enable data interoperability. Many studies provide implementation guidelines, assessment metrics, and software to achieve FAIR-compliant data, especially for health data sets. Health Level 7 (HL7) Fast Healthcare Interoperability Resources (FHIR) is a health data content modeling and exchange standard. Objective Our goal was to devise a new methodology to extract, transform, and load existing health data sets into HL7 FHIR repositories in line with FAIR principles, develop a Data Curation Tool to implement the methodology, and evaluate it on health data sets from 2 different but complementary institutions. We aimed to increase the level of compliance with FAIR principles of existing health data sets through standardization and facilitate health data sharing by eliminating the associated technical barriers. Methods Our approach automatically processes the capabilities of a given FHIR end point and directs the user while configuring mappings according to the rules enforced by FHIR profile definitions. Code system mappings can be configured for terminology translations through automatic use of FHIR resources. The validity of the created FHIR resources can be automatically checked, and the software does not allow invalid resources to be persisted. At each stage of our data transformation methodology, we used particular FHIR-based techniques so that the resulting data set could be evaluated as FAIR. We performed a data-centric evaluation of our methodology on health data sets from 2 different institutions. Results Through an intuitive graphical user interface, users are prompted to configure the mappings into FHIR resource types with respect to the restrictions of selected profiles. Once the mappings are developed, our approach can syntactically and semantically transform existing health data sets into HL7 FHIR without loss of data utility according to our privacy-concerned criteria. In addition to the mapped resource types, behind the scenes, we create additional FHIR resources to satisfy several FAIR criteria. According to the data maturity indicators and evaluation methods of the FAIR Data Maturity Model, we achieved the maximum level (level 5) for being Findable, Accessible, and Interoperable and level 3 for being Reusable. Conclusions We developed and extensively evaluated our data transformation approach to unlock the value of existing health data residing in disparate data silos to make them available for sharing according to the FAIR principles. We showed that our method can successfully transform existing health data sets into HL7 FHIR without loss of data utility, and the result is FAIR in terms of the FAIR Data Maturity Model. We support institutional migration to HL7 FHIR, which not only leads to FAIR data sharing but also eases the integration with different research networks.},
  pmcid = {PMC10034606},
  pmid = {36884270},
  file = {/Users/dkapitan/Zotero/storage/TV2QS7X7/Sinaci et al. - 2023 - A Data Transformation Methodology to Create Findab.pdf}
}

@article{solum2003layers,
  title = {The {{Layers Principle}}: {{Internet Architecture}} and the {{Law}}},
  shorttitle = {The {{Layers Principle}}},
  author = {Solum, Lawrence B. and Chung, Minn},
  year = {2003},
  journal = {SSRN Electronic Journal},
  issn = {1556-5068},
  doi = {10.2139/ssrn.416263},
  urldate = {2024-08-13},
  langid = {english},
  file = {/Users/dkapitan/Zotero/storage/7TX2P39E/Solum and Chung - 2003 - The Layers Principle Internet Architecture and th.pdf}
}

@misc{sql-on-fhir,
  title = {{{SQL}} on {{FHIR}} Speciification v0.0.1-Pre},
  year = {2024},
  month = mar,
  urldate = {2024-01-18},
  howpublished = {https://build.fhir.org/ig/FHIR/sql-on-fhir-v2/},
  file = {/Users/dkapitan/Zotero/storage/4VQPEDL7/sql-on-fhir-v2.html}
}

@misc{summitinstitutefordevelopment2023bunda,
  title = {{{BUNDA App}}},
  author = {{Summit Institute for Development}},
  year = {2023},
  month = may,
  journal = {Summit Institute},
  urldate = {2024-01-18},
  abstract = {Summit Institute for Development works closely with partners to develop cuffless optical BP measurement (OptiBP) integrated with antenatal decision-support and client tracking (BUNDA App) to improve health provider performance to detect hypertension and improve pregnancy outcomes. In this video, one of the village midwives in Lombok, West Nusa Tenggara, Indonesia, was sharing her experiences of using the BUNDA App. Please join us in making the best care for maternal and child health services. We},
  howpublished = {https://www.sid-indonesia.org/post/bunda-app},
  langid = {english},
  file = {/Users/dkapitan/Zotero/storage/RLAL2KAQ/bunda-app.html}
}

@article{swartout1982inevitable,
  title = {On the Inevitable Intertwining of Specification and Implementation},
  author = {Swartout, William and Balzer, Robert},
  year = {1982},
  month = jul,
  journal = {Communications of the ACM},
  volume = {25},
  number = {7},
  pages = {438--440},
  issn = {0001-0782, 1557-7317},
  doi = {10.1145/358557.358572},
  urldate = {2024-01-09},
  abstract = {Contrary to recent claims that specification should be completed before implementation begins, this paper presents two arguments that the two processes must be intertwined. First, limitations of available implementation technology may force a specification change. For example, deciding to implement a stack as an array (rather than as a linked list) may impose a fixed limit on the depth of the stack. Second, implementation choices may suggest augmentations to the original specification. For example, deciding to use an existing pattern-match routine to implement the search command in an editor may lead to incorporating some of the routine's features into the specification, such as the ability to include wild cards in the search key. This paper elaborates these points and illustrates how they arise in the specification of a controller for a package router.},
  langid = {english},
  file = {/Users/dkapitan/Zotero/storage/YX6SLIC2/Swartout and Balzer - 1982 - On the inevitable intertwining of specification an.pdf}
}

@article{syzdykova2017opensource,
  title = {Open-{{Source Electronic Health Record Systems}} for {{Low-Resource Settings}}: {{Systematic Review}}},
  shorttitle = {Open-{{Source Electronic Health Record Systems}} for {{Low-Resource Settings}}},
  author = {Syzdykova, Assel and Malta, Andr{\'e} and Zolfo, Maria and Diro, Ermias and Oliveira, Jos{\'e} Luis},
  year = {2017},
  month = nov,
  journal = {JMIR Medical Informatics},
  volume = {5},
  number = {4},
  pages = {e44},
  issn = {2291-9694},
  doi = {10.2196/medinform.8131},
  abstract = {Background Despite the great impact of information and communication technologies on clinical practice and on the quality of health services, this trend has been almost exclusive to developed countries, whereas countries with poor resources suffer from many economic and social issues that have hindered the real benefits of electronic health (eHealth) tools. As a component of eHealth systems, electronic health records (EHRs) play a fundamental role in patient management and effective medical care services. Thus, the adoption of EHRs in regions with a lack of infrastructure, untrained staff, and ill-equipped health care providers is an important task. However, the main barrier to adopting EHR software in low- and middle-income countries is the cost of its purchase and maintenance, which highlights the open-source approach as a good solution for these underserved areas. Objective The aim of this study was to conduct a systematic review of open-source EHR systems based on the requirements and limitations of low-resource settings. Methods First, we reviewed existing literature on the comparison of available open-source solutions. In close collaboration with the University of Gondar Hospital, Ethiopia, we identified common limitations in poor resource environments and also the main requirements that EHRs should support. Then, we extensively evaluated the current open-source EHR solutions, discussing their strengths and weaknesses, and their appropriateness to fulfill a predefined set of features relevant for low-resource settings. Results The evaluation methodology allowed assessment of several key aspects of available solutions that are as follows: (1) integrated applications, (2) configurable reports, (3) custom reports, (4) custom forms, (5) interoperability, (6) coding systems, (7) authentication methods, (8) patient portal, (9) access control model, (10) cryptographic features, (11) flexible data model, (12) offline support, (13) native client, (14) Web client,(15) other clients, (16) code-based language, (17) development activity, (18) modularity, (19) user interface, (20) community support, and (21) customization. The quality of each feature is discussed for each of the evaluated solutions and a final comparison is presented. Conclusions There is a clear demand for open-source, reliable, and flexible EHR systems in low-resource settings. In this study, we have evaluated and compared five open-source EHR systems following a multidimensional methodology that can provide informed recommendations to other implementers, developers, and health care professionals. We hope that the results of this comparison can guide decision making when needing to adopt, install, and maintain an open-source EHR solution in low-resource settings.},
  pmcid = {PMC5703976},
  pmid = {29133283},
  file = {/Users/dkapitan/Zotero/storage/FRAHQRX5/Syzdykova et al. - 2017 - Open-Source Electronic Health Record Systems for L.pdf}
}

@misc{tabular,
  title = {Tabular -- {{An}} Independent Storage Engine from the Creators of {{Apache Iceberg}}},
  urldate = {2024-03-26},
  howpublished = {https://tabular.io/},
  file = {/Users/dkapitan/Zotero/storage/5AF49JIK/tabular.io.html}
}

@article{taylor2023search,
  title = {In {{Search}} of {{Public Values}} in {{Private Systems}}: {{A Response}} to the {{Montesquieu Lecture}} by {{Karen Yeung}}},
  shorttitle = {In {{Search}} of {{Public Values}} in {{Private Systems}}},
  author = {Taylor, Linnet},
  year = {2023},
  month = feb,
  journal = {Tilburg Law Review},
  volume = {27},
  number = {2},
  pages = {50--55},
  issn = {2211-2545},
  doi = {10.5334/tilr.305},
  urldate = {2024-02-26},
  langid = {english},
  file = {/Users/dkapitan/Zotero/storage/SGVGHW68/Taylor - 2023 - In Search of Public Values in Private Systems A R.pdf}
}

@article{taylor2023why,
  title = {Why Are Sector Transgressions so Hard to Govern? {{Reflections}} from {{Europe}}'s Pandemic Experience},
  shorttitle = {Why Are Sector Transgressions so Hard to Govern?},
  author = {Taylor, Linnet and Martin, Aaron and {de Souza}, Siddharth Peter and {Lopez-Solano}, Joan},
  year = {2023},
  journal = {Information, Communication \& Society},
  volume = {0},
  number = {0},
  pages = {1--5},
  publisher = {Routledge},
  issn = {1369-118X},
  doi = {10.1080/1369118X.2023.2264919},
  urldate = {2024-02-26},
  abstract = {In this commentary, we address the notion of `sector transgressions', which we define as a problem of infrastructural power with features of regulatory capture. During the pandemic, new markets were created for public service provision in many fields, including but not limited to public health, and governments in the EU decreased regulatory controls on the private provision of public services. The results included increased government readiness to accept economic and political dependencies in return for efficiencies provided by large-scale infrastructures; decreased resistance among the general public to the private-sector takeover of what had been public tasks, and a corresponding lack of transparency about procurement and the alliances being made. We examine the features of these sector transgressions which make them difficult for civil society to resist, namely the instrumentalisation of privacy and data protection, the legalisation of transgressions through the decrease in regulatory controls, and the attractiveness to government of cheap and efficient infrastructural underpinnings to public services.},
  keywords = {big data,COVID-19,Infrastructures,legitimacy,political economy,regulation},
  file = {/Users/dkapitan/Zotero/storage/DHFMDMF6/Taylor et al. - 2023 - Why are sector transgressions so hard to govern R.pdf}
}

@techreport{tilahun2023african,
  title = {African {{Union Health Information Exchange Guidelines}} and {{Standards}}},
  author = {Tilahun, Binyam and Mamuye, Adane and Yilma, Tesfahun and Shehata, Yasser},
  year = {2023},
  month = mar,
  abstract = {The application of digital health technology is growing at a rapid rate in Africa, with the goals of improving the delivery of healthcare services and more effectively reaching out to remote and underserved communities. The lack of enabling guidelines and standards across the continent, on the other hand, makes it difficult to share data in a meaningful way across the continent. Considering this, Africa Centres for Disease Control and Prevention (Africa CDC) established a task force of 24 members to provide expertise and guidance in the development of AU HIE guidelines and standards. Members of the task force were subject matter experts working in Africa and internationally on the collection, analysis, and exchange of health information. Some of these experts had been involved in previous consultations on defining Africa CDC's health information systems strategy. A chairperson, co-chairperson, and secretary were elected to engage the task force members in different technical working groups. The technical leadership and coordination of this work was done by the University of Gondar and HISP SA. A chairperson, co-chairperson, and secretary were elected to engage the task force members. Three technical working groups were constituted to lead the drafting of the three sections of the document: 1. HIE Policy directions 2. HIE Standards 3. Implementation Use Cases Following several virtual meetings and consultations, a draft document on AU HIE guidelines and standards was developed. The methodology employed involved the reviewing of scientific publications and governmental reports on HIE guidelines and standards in Africa; reviewing Internationally known comprehensive and robust data exchange standards; and incorporating recommendations from the Africa CDC HIE Task Force Members. Additionally, the document was critically reviewed and validated by Member States in all AU regions through several validation workshops; West Africa (validation workshop took place in Senegal), Central Africa (Congo-Brazaville), East Africa (Rwanda), South Africa (Namibia) and North Africa (Mauritania) through validation workshops. Representatives of Africa CDC, Regional},
  file = {/Users/dkapitan/Zotero/storage/94KNBUND/Tilahun et al. - 2023 - African Union Health Information Exchange Guidelin.pdf}
}

@article{till2023digital,
  title = {Digital {{Health Technologies}} for {{Maternal}} and {{Child Health}} in {{Africa}} and {{Other Low-}} and {{Middle-Income Countries}}: {{Cross-disciplinary Scoping Review With Stakeholder Consultation}}},
  shorttitle = {Digital {{Health Technologies}} for {{Maternal}} and {{Child Health}} in {{Africa}} and {{Other Low-}} and {{Middle-Income Countries}}},
  author = {Till, Sarina and Mkhize, Mirriam and Farao, Jaydon and Shandu, Londiwe Deborah and Muthelo, Livhuwani and Coleman, Toshka Lauren and Mbombi, Masenyani and Bopape, Mamara and Klingberg, Sonja and van Heerden, Alastair and Mothiba, Tebogo and Densmore, Melissa and Dias, Nervo Xavier Verdezoto and Network, CoMaCH},
  year = {2023},
  month = apr,
  journal = {Journal of Medical Internet Research},
  volume = {25},
  number = {1},
  pages = {e42161},
  publisher = {JMIR Publications Inc., Toronto, Canada},
  doi = {10.2196/42161},
  urldate = {2024-08-22},
  abstract = {Background: Maternal and child health (MCH) is a global health concern, especially impacting low- and middle-income countries (LMIC). Digital health technologies are creating opportunities to address the social determinants of MCH by facilitating access to information and providing other forms of support throughout the maternity journey. Previous reviews in different disciplines have synthesized digital health intervention outcomes in LMIC. However, contributions in this space are scattered across publications in different disciplines and lack coherence in what digital MCH means across fields. Objective: This cross-disciplinary scoping review synthesized the existing published literature in 3 major disciplines on the use of digital health interventions for MCH in LMIC, with a particular focus on sub-Saharan Africa. Methods: We conducted a scoping review using the 6-stage framework by Arksey and O'Malley across 3 disciplines, including public health, social sciences applied to health, and human-computer interaction research in health care. We searched the following databases: Scopus, PubMed, Google Scholar, ACM Digital Library, IEEE Xplore, Web of Science, and PLOS. A stakeholder consultation was undertaken to inform and validate the review. Results: During the search, 284 peer-reviewed articles were identified. After removing 41 duplicates, 141 articles met our inclusion criteria: 34 from social sciences applied to health, 58 from public health, and 49 from human-computer interaction research in health care. These articles were then tagged (labeled) by 3 researchers using a custom data extraction framework to obtain the findings. First, the scope of digital MCH was found to target health education (eg, breastfeeding and child nutrition), care and follow-up of health service use (to support community health workers), maternal mental health, and nutritional and health outcomes. These interventions included mobile apps, SMS text messaging, voice messaging, web-based applications, social media, movies and videos, and wearable or sensor-based devices. Second, we highlight key challenges: little attention has been given to understanding the lived experiences of the communities; key role players (eg, fathers, grandparents, and other family members) are often excluded; and many studies are designed considering nuclear families that do not represent the family structures of the local cultures. Conclusions: Digital MCH has shown steady growth in Africa and other LMIC settings. Unfortunately, the role of the community was negligible, as these interventions often do not include communities early and inclusively enough in the design process. We highlight key opportunities and sociotechnical challenges for digital MCH in LMIC, such as more affordable mobile data; better access to smartphones and wearable technologies; and the rise of custom-developed, culturally appropriate apps that are more suited to low-literacy users. We also focus on barriers such as an overreliance on text-based communications and the difficulty of MCH research and design to inform and translate into policy.},
  langid = {english},
  file = {/Users/dkapitan/Zotero/storage/NL6RYLLC/Till et al. - 2023 - Digital Health Technologies for Maternal and Child.pdf;/Users/dkapitan/Zotero/storage/WS7432TR/e42161.html}
}

@article{torab-miandoab2023interoperability,
  title = {Interoperability of Heterogeneous Health Information Systems: A Systematic Literature Review},
  shorttitle = {Interoperability of Heterogeneous Health Information Systems},
  author = {{Torab-Miandoab}, Amir and {Samad-Soltani}, Taha and Jodati, Ahmadreza and {Rezaei-Hachesu}, Peyman},
  year = {2023},
  month = jan,
  journal = {BMC Medical Informatics and Decision Making},
  volume = {23},
  pages = {18},
  issn = {1472-6947},
  doi = {10.1186/s12911-023-02115-5},
  urldate = {2024-08-20},
  abstract = {Background The lack of interoperability between health information systems reduces the quality of care provided to patients and wastes resources. Accordingly, there is an urgent need to develop integration mechanisms among the various health information systems. The aim of this review was to investigate the interoperability requirements for heterogeneous health information systems and to summarize and present them. Methods In accordance with the PRISMA guideline, a broad electronic search of all literature was conducted on the topic through six databases, including PubMed, Web of science, Scopus, MEDLINE, Cochrane Library and Embase to 25 July 2022. The inclusion criteria were to select English-written articles available in full text with the closest objectives. 36 articles were selected for further analysis. Results Interoperability has been raised in the field of health information systems from 2003 and now it is one of the topics of interest to researchers. The projects done in this field are mostly in the national scope and to achieve the electronic health record. HL7 FHIR, CDA, HIPAA and SNOMED-CT, SOA, RIM, XML, API, JAVA and SQL are among the most important requirements for implementing interoperability. In order to guarantee the concept of data exchange, semantic interaction is the best choice because the systems can recognize and process semantically similar information homogeneously. Conclusions The health industry has become more complex and has new needs. Interoperability meets this needs by communicating between the output and input of processor systems and making easier to access the data in the required formats. Supplementary Information The online version contains supplementary material available at 10.1186/s12911-023-02115-5.},
  pmcid = {PMC9875417},
  pmid = {36694161},
  file = {/Users/dkapitan/Zotero/storage/EFKGRWHM/Torab-Miandoab et al. - 2023 - Interoperability of heterogeneous health information systems a systematic literature review.pdf}
}

@misc{tsafnat2024converge,
  title = {Converge or Collide? {{Making}} Sense of a Plethora of Open Data Standards in Healthcare: An Editorial},
  shorttitle = {Converge or Collide?},
  author = {Tsafnat, G and Dunscombe, R and Gabriel, D and Grieve, G and Reich, C},
  year = {2024},
  urldate = {2024-04-02},
  abstract = {Journal of Medical Internet Research - International Scientific Journal for Medical Research, Information and Communication on the Internet},
  langid = {english},
  file = {/Users/dkapitan/Zotero/storage/GY4ZUVLW/Tsafnat et al. - 2024 - Converge or collide Making sense of a plethora of.pdf;/Users/dkapitan/Zotero/storage/T9XNXKSN/55779.html}
}

@misc{tzhea2020,
  title = {Tanzania {{Health Enterprise Architecture}}},
  year = {2020},
  urldate = {2023-06-12},
  file = {/Users/dkapitan/Zotero/storage/EX2Z9DG2/Tanzania Health Enterprise Architecture 20202.pdf}
}

@article{unkels2023understanding,
  title = {Understanding Maternity Care Providers' Use of Data in {{Southern Tanzania}}},
  author = {Unkels, Regine and {Alwy Al-Beity}, Fadhlun and Julius, Zamoyoni and Mkumbo, Elibariki and Pembe, Andrea B and Hanson, Claudia and {Molsted-Alvesson}, Helle},
  year = {2023},
  month = jan,
  journal = {BMJ Global Health},
  volume = {8},
  number = {1},
  pages = {e010937},
  issn = {2059-7908},
  doi = {10.1136/bmjgh-2022-010937},
  urldate = {2024-02-27},
  abstract = {Introduction Health information management system data is collected for national planning and evaluation but is rarely used for healthcare improvements at subnational or facility-level in low-and-middle-income countries. Research suggests that perceived data quality and lack of feedback are contributing factors. We aimed to understand maternity care providers' perceptions of data and how they use it, with a view to co-design interventions to improve data quality and use. Methods We based our research on constructivist grounded theory. We conducted 14 in-depth interviews, two focus group discussions with maternity care providers and 48 hours of observations in maternity wards to understand maternity providers' interaction with data in two rural hospitals in Southern Tanzania. Constant comparative data analysis was applied to develop initial and focused codes, subcategories and categories were continuously validated through peer and member checks. Results Maternity care providers found routine health information data of little use to reconcile demands from managers, the community and their challenging working environment within their daily work. They thus added informal narrative documentation sources. They created alternative narratives through data of a maternity care where mothers and babies were safeguarded. The resulting documentation system, however, led to duplication and increased systemic complexity. Conclusions Current health information systems may not meet all data demands of maternity care providers, or other healthcare workers. Policy makers and health information system specialists need to acknowledge different ways of data use beyond health service planning, with an emphasis on healthcare providers' data needs for clinical documentation.},
  pmcid = {PMC9827191},
  pmid = {36609348},
  file = {/Users/dkapitan/Zotero/storage/4ZFW52IW/Unkels et al. - 2023 - Understanding maternity care providers’ use of dat.pdf}
}

@article{venable2016feds,
  title = {{{FEDS}}: A {{Framework}} for {{Evaluation}} in {{Design Science Research}}},
  shorttitle = {{{FEDS}}},
  author = {Venable, John and {Pries-Heje}, Jan and Baskerville, Richard},
  year = {2016},
  month = jan,
  journal = {European Journal of Information Systems},
  volume = {25},
  number = {1},
  pages = {77--89},
  issn = {1476-9344},
  doi = {10.1057/ejis.2014.36},
  urldate = {2024-02-07},
  abstract = {Evaluation of design artefacts and design theories is a key activity in Design Science Research (DSR), as it provides feedback for further development and (if done correctly) assures the rigour of the research. However, the extant DSR literature provides insufficient guidance on evaluation to enable Design Science Researchers to effectively design and incorporate evaluation activities into a DSR project that can achieve DSR goals and objectives. To address this research gap, this research paper develops, explicates, and provides evidence for the utility of a Framework for Evaluation in Design Science (FEDS) together with a process to guide design science researchers in developing a strategy for evaluating the artefacts they develop within a DSR project. A FEDS strategy considers why, when, how, and what to evaluate. FEDS includes a two-dimensional characterisation of DSR evaluation episodes (particular evaluations), with one dimension being the functional purpose of the evaluation (formative or summative) and the other dimension being the paradigm of the evaluation (artificial or naturalistic). The FEDS evaluation design process is comprised of four steps: (1) explicate the goals of the evaluation, (2) choose the evaluation strategy or strategies, (3) determine the properties to evaluate, and (4) design the individual evaluation episode(s). The paper illustrates the framework with two examples and provides evidence of its utility via a naturalistic, summative evaluation through its use on an actual DSR project.},
  langid = {english},
  keywords = {artefact evaluation,Design Science Research,information systems evaluation,research design,research methodology,utility evaluation},
  file = {/Users/dkapitan/Zotero/storage/C42M7QGN/Venable et al. - 2016 - FEDS a Framework for Evaluation in Design Science.pdf}
}

@article{vorisek2022fast,
  title = {Fast {{Healthcare Interoperability Resources}} ({{FHIR}}) for {{Interoperability}} in {{Health Research}}: {{Systematic Review}}},
  shorttitle = {Fast {{Healthcare Interoperability Resources}} ({{FHIR}}) for {{Interoperability}} in {{Health Research}}},
  author = {Vorisek, Carina Nina and Lehne, Moritz and Klopfenstein, Sophie Anne Ines and Mayer, Paula Josephine and Bartschke, Alexander and Haese, Thomas and Thun, Sylvia},
  year = {2022},
  month = jul,
  journal = {JMIR Medical Informatics},
  volume = {10},
  number = {7},
  pages = {e35724},
  publisher = {JMIR Publications Inc., Toronto, Canada},
  doi = {10.2196/35724},
  urldate = {2023-02-16},
  abstract = {Background: The standard Fast Healthcare Interoperability Resources (FHIR) is widely used in health information technology. However, its use as a standard for health research is still less prevalent. To use existing data sources more efficiently for health research, data interoperability becomes increasingly important. FHIR provides solutions by offering resource domains such as ``Public Health \&amp; Research'' and ``Evidence-Based Medicine'' while using already established web technologies. Therefore, FHIR could help standardize data across different data sources and improve interoperability in health research. Objective: The aim of our study was to provide a systematic review of existing literature and determine the current state of FHIR implementations in health research and possible future directions. Methods: We searched the PubMed/MEDLINE, Embase, Web of Science, IEEE Xplore, and Cochrane Library databases for studies published from 2011 to 2022. Studies investigating the use of FHIR in health research were included. Articles published before 2011, abstracts, reviews, editorials, and expert opinions were excluded. We followed the PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) guidelines and registered this study with PROSPERO (CRD42021235393). Data synthesis was done in tables and figures. Results: We identified a total of 998 studies, of which 49 studies were eligible for inclusion. Of the 49 studies, most (73\%, n=36) covered the domain of clinical research, whereas the remaining studies focused on public health or epidemiology (6\%, n=3) or did not specify their research domain (20\%, n=10). Studies used FHIR for data capture (29\%, n=14), standardization of data (41\%, n=20), analysis (12\%, n=6), recruitment (14\%, n=7), and consent management (4\%, n=2). Most (55\%, 27/49) of the studies had a generic approach, and 55\% (12/22) of the studies focusing on specific medical specialties (infectious disease, genomics, oncology, environmental health, imaging, and pulmonary hypertension) reported their solutions to be conferrable to other use cases. Most (63\%, 31/49) of the studies reported using additional data models or terminologies: Systematized Nomenclature of Medicine Clinical Terms (29\%, n=14), Logical Observation Identifiers Names and Codes (37\%, n=18), International Classification of Diseases 10th Revision (18\%, n=9), Observational Medical Outcomes Partnership common data model (12\%, n=6), and others (43\%, n=21). Only 4 (8\%) studies used a FHIR resource from the domain ``Public Health \&amp; Research.'' Limitations using FHIR included the possible change in the content of FHIR resources, safety, legal matters, and the need for a FHIR server. Conclusions: Our review found that FHIR can be implemented in health research, and the areas of application are broad and generalizable in most use cases. The implementation of international terminologies was common, and other standards such as the Observational Medical Outcomes Partnership common data model could be used as a complement to FHIR. Limitations such as the change of FHIR content, lack of FHIR implementation, safety, and legal matters need to be addressed in future releases to expand the use of FHIR and, therefore, interoperability in health research.},
  copyright = {This is an open-access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work, first published JMIR Medical Informatics, is properly cited. The complete bibliographic information, a link to the original publication on https://medinform.jmir.org/, as well as this copyright and license information must be included.},
  langid = {english},
  file = {/Users/dkapitan/Zotero/storage/VTR494NX/Vorisek et al. - 2022 - Fast Healthcare Interoperability Resources (FHIR) .pdf;/Users/dkapitan/Zotero/storage/X5PFULH8/e35724.html}
}

@article{watson2008business,
  title = {The Business of Open Source},
  author = {Watson, Richard T. and Boudreau, Marie-Claude and York, Paul T. and Greiner, Martina E. and Wynn, Donald},
  year = {2008},
  month = apr,
  journal = {Communications of the ACM},
  volume = {51},
  number = {4},
  pages = {41--46},
  issn = {0001-0782, 1557-7317},
  doi = {10.1145/1330311.1330321},
  urldate = {2024-02-29},
  abstract = {Tracking the changing competitive conditions of the software industry.},
  langid = {english},
  file = {/Users/dkapitan/Zotero/storage/A79YRZZM/Watson et al. - 2008 - The business of open source.pdf}
}

@techreport{who2019recommendations,
  title = {Recommendations on Digital Interventions for Health System Strengthening},
  author = {{World Health Organization}},
  year = {2019},
  institution = {World Health Organization},
  abstract = {This guideline urges readers to recognize that digital health interventions are not a substitute for functioning health systems, and that there are significant limitations to what digital health is able to address.},
  langid = {english},
  file = {/Users/dkapitan/Zotero/storage/2EV55EIV/Organization - 2019 - Recommendations on digital interventions for healt.pdf}
}

@techreport{who2021global,
  title = {Global Strategy on Digital Health 2020-2025},
  author = {{World Health Organization}},
  year = {2021},
  month = nov,
  pages = {1031--1126},
  address = {Geneva},
  institution = {World Health Organization},
  langid = {english},
  keywords = {Atmosphere,Cardiovascular Diseases,Child Development,COVID-19,Enterobiasis,Evidence and Research,Health Services Research,Information,Metabolic Syndrome,Noncommunicable Diseases,Telemedicine,Typhoid Fever},
  file = {/Users/dkapitan/Zotero/storage/YLLDMH24/World Health Organization - 2021 - Global strategy on digital health 2020-2025.pdf}
}

@article{witter2022learning,
  title = {Learning Health Systems in Low-Income and Middle-Income Countries: Exploring Evidence and Expert Insights},
  shorttitle = {Learning Health Systems in Low-Income and Middle-Income Countries},
  author = {Witter, Sophie and Sheikh, Kabir and Schleiff, Meike},
  year = {2022},
  month = sep,
  journal = {BMJ Global Health},
  volume = {7},
  number = {Suppl 7},
  pages = {e008115},
  publisher = {BMJ Specialist Journals},
  issn = {2059-7908},
  doi = {10.1136/bmjgh-2021-008115},
  urldate = {2024-09-06},
  abstract = {Introduction Learning health systems (LHS) is a multifaceted subject. This paper reviewed current concepts as well as real-world experiences of LHS, drawing on published and unpublished knowledge in order to identify and describe important principles and practices that characterise LHS in low/middle-income country (LMIC) settings. Methods We adopted an exploratory approach to the literature review, recognising there are limited studies that focus specifically on system-wide learning in LMICs, but a vast set of connected bodies of literature. 116 studies were included, drawn from an electronic literature search of published and grey literature. In addition, 17 interviews were conducted with health policy and research experts to gain experiential knowledge. Results The findings were structured by eight domains on learning enablers. All of these interact with one another and influence actors from community to international levels.We found that learning comes from the connection between information, deliberation, and action. Moreover, these processes occur at different levels. It is therefore important to consider experiential knowledge from multiple levels and experiences. Creating spaces and providing resources for communities, staff and managers to deliberate on their challenges and find solutions has political implications, however, and is challenging, particularly when resources are constrained, funding and accountability are fragmented and the focus is short-term and narrow. Nevertheless, we can learn from countries that have managed to develop institutional mechanisms and human capacities which help health systems respond to changing environments with `best fit' solutions. Conclusion Health systems are knowledge producers, but learning is not automatic. It needs to be valued and facilitated. Everyday governance of health systems can create spaces for reflective practice and learning within routine processes at different levels. This article highlights important enablers, but there remains much work to be done on developing this field of knowledge.},
  chapter = {Original research},
  copyright = {{\copyright} Author(s) (or their employer(s)) 2022. Re-use permitted under CC BY-NC. No commercial re-use. See rights and permissions. Published by BMJ.. http://creativecommons.org/licenses/by-nc/4.0/This is an open access article distributed in accordance with the Creative Commons Attribution Non Commercial (CC BY-NC 4.0) license, which permits others to distribute, remix, adapt, build upon this work non-commercially, and license their derivative works on different terms, provided the original work is properly cited, appropriate credit is given, any changes made indicated, and the use is non-commercial. See:~http://creativecommons.org/licenses/by-nc/4.0/.},
  langid = {english},
  pmid = {36130793},
  keywords = {health policy,health services research,health systems,health systems evaluation,review},
  file = {/Users/dkapitan/Zotero/storage/Z68Y6HEH/Witter et al. - 2022 - Learning health systems in low-income and middle-i.pdf}
}

@article{wong2022applying,
  title = {Applying {{Machine Learning}} in {{Distributed Data Networks}} for {{Pharmacoepidemiologic}} and {{Pharmacovigilance Studies}}: {{Opportunities}}, {{Challenges}}, and {{Considerations}}},
  shorttitle = {Applying {{Machine Learning}} in {{Distributed Data Networks}} for {{Pharmacoepidemiologic}} and {{Pharmacovigilance Studies}}},
  author = {Wong, Jenna and {Prieto-Alhambra}, Daniel and Rijnbeek, Peter R. and Desai, Rishi J. and Reps, Jenna M. and Toh, Sengwee},
  year = {2022},
  month = may,
  journal = {Drug Safety},
  volume = {45},
  number = {5},
  pages = {493--510},
  issn = {1179-1942},
  doi = {10.1007/s40264-022-01158-3},
  urldate = {2024-05-27},
  abstract = {Increasing availability of electronic health databases capturing real-world experiences with medical products has garnered much interest in their use for pharmacoepidemiologic and pharmacovigilance studies. The traditional practice of having numerous groups use single databases to accomplish similar tasks and address common questions about medical products can be made more efficient through well-coordinated multi-database studies, greatly facilitated through distributed data network (DDN) architectures. Access to larger amounts of electronic health data within DDNs has created a growing interest in using data-adaptive machine learning (ML) techniques that can automatically model complex associations in high-dimensional data with minimal human guidance. However, the siloed storage and diverse nature of the databases in DDNs create unique challenges for using ML. In this paper, we discuss opportunities, challenges, and considerations for applying ML in DDNs for pharmacoepidemiologic and pharmacovigilance studies. We first discuss major types of activities performed by DDNs and how ML may be used. Next, we discuss practical data-related factors influencing how DDNs work in practice. We then combine these discussions and jointly consider how opportunities for ML are affected by practical data-related factors for DDNs, leading to several challenges. We present different approaches for addressing these challenges and highlight efforts that real-world DDNs have taken or are currently taking to help mitigate them. Despite these challenges, the time is ripe for the emerging interest to use ML in DDNs, and the utility of these data-adaptive modeling techniques in pharmacoepidemiologic and pharmacovigilance studies will likely continue to increase in the coming years.},
  langid = {english},
  file = {/Users/dkapitan/Zotero/storage/2ECJEHLE/Wong et al. - 2022 - Applying Machine Learning in Distributed Data Netw.pdf}
}

@article{xu2020fhir,
  title = {{{FHIR PIT}}: An Open Software Application for Spatiotemporal Integration of Clinical Data and Environmental Exposures Data},
  shorttitle = {{{FHIR PIT}}},
  author = {Xu, Hao and Cox, Steven and Stillwell, Lisa and Pfaff, Emily and Champion, James and Ahalt, Stanley C. and Fecho, Karamarie},
  year = {2020},
  month = mar,
  journal = {BMC Medical Informatics and Decision Making},
  volume = {20},
  number = {1},
  pages = {53},
  issn = {1472-6947},
  doi = {10.1186/s12911-020-1056-9},
  urldate = {2024-01-09},
  abstract = {Informatics tools to support the integration and subsequent interrogation of spatiotemporal data such as clinical data and environmental exposures data are lacking. Such tools are needed to support research in environmental health and any biomedical field that is challenged by the need for integrated spatiotemporal data to examine individual-level determinants of health and disease.},
  keywords = {Data integration,Modular software design,Spatiotemporal data},
  file = {/Users/dkapitan/Zotero/storage/AQJAPX6N/Xu et al. - 2020 - FHIR PIT an open software application for spatiot.pdf}
}

@article{xu2021federated,
  title = {Federated {{Learning}} for {{Healthcare Informatics}}},
  author = {Xu, Jie and Glicksberg, Benjamin S. and Su, Chang and Walker, Peter and Bian, Jiang and Wang, Fei},
  year = {2021},
  month = mar,
  journal = {Journal of Healthcare Informatics Research},
  volume = {5},
  number = {1},
  pages = {1--19},
  issn = {2509-498X},
  doi = {10.1007/s41666-020-00082-4},
  urldate = {2024-05-27},
  abstract = {With the rapid development of computer software and hardware technologies, more and more healthcare data are becoming readily available from clinical institutions, patients, insurance companies, and pharmaceutical industries, among others. This access provides an unprecedented opportunity for data science technologies to derive data-driven insights and improve the quality of care delivery. Healthcare data, however, are usually fragmented and private making it difficult to generate robust results across populations. For example, different hospitals own the electronic health records (EHR) of different patient populations and these records are difficult to share across hospitals because of their sensitive nature. This creates a big barrier for developing effective analytical approaches that are generalizable, which need diverse, ``big data.'' Federated learning, a mechanism of training a shared global model with a central server while keeping all the sensitive data in local institutions where the data belong, provides great promise to connect the fragmented healthcare data sources with privacy-preservation. The goal of this survey is to provide a review for federated learning technologies, particularly within the biomedical space. In particular, we summarize the general solutions to the statistical challenges, system challenges, and privacy issues in federated learning, and point out the implications and potentials in healthcare.},
  langid = {english},
  keywords = {Federated learning,Healthcare,Privacy},
  file = {/Users/dkapitan/Zotero/storage/M6EF8PEB/Xu et al. - 2021 - Federated Learning for Healthcare Informatics.pdf}
}

@article{yeung2023new,
  title = {The {{New Public Analytics}} as an {{Emerging Paradigm}} in {{Public Sector Administration}}},
  author = {Yeung, Karen},
  year = {2023},
  month = feb,
  journal = {Tilburg Law Review},
  volume = {27},
  number = {2},
  issn = {2211-2545},
  doi = {10.5334/tilr.303},
  urldate = {2024-08-27},
  abstract = {The Tilburg Law Review is an open access law journal embedded in the Tilburg Law School, consistently ranked as a top law school in the Netherlands and internationally. The review hosts the Montesquieu Lectures, the yearly public lectures of the Tilburg Law School. It also hosts one special issue a year on a topic related to one of the research Signature Plans of the Tilburg Law School. For more information about the journal's scope, see our About page},
  langid = {american},
  file = {/Users/dkapitan/Zotero/storage/YSMKZ444/Yeung - 2023 - The New Public Analytics as an Emerging Paradigm i.pdf}
}

@misc{zegers2023how,
  type = {Info:Eu-Repo/Semantics/{{bachelorThesis}}},
  title = {How to Capture Maximum Value through Minimizing Transaction Costs for a Digital {{E-healthcare}} Platform},
  author = {Zegers, Jelle},
  year = {2023},
  publisher = {University of Twente},
  urldate = {2024-08-13},
  abstract = {With the increasing pressure on healthcare systems and the growing importance of preventive healthcare, platforms like Samen Kwiek have emerged to connect service providers and users in rural areas, aiming to enhance economic growth and improve citizens' quality of life. To maximize the value generated by the platform and ensure its long-term sustainability, understanding the interplay between platforms, value capture, and transaction costs is crucial. This study is theoretically grounded in the frameworks of platform business models, transaction cost theory, and value capture. The platform business model approach highlights the role of intermediaries in efficiently linking actors in a multi-sided platform, while transaction cost theory explores the costs associated with transacting in markets and strategies to minimize them. The research focuses on three key dimensions of transaction cost theory: transaction frequency, asset specificity, and uncertainty. Transaction frequency examines the frequency of exchanges between actors on the platform, while asset specificity explores the level of investment customization for specific transactions. Uncertainty assesses the extent to which information sharing and detailed service information reduce information asymmetry among participants. These dimensions have been measured before and after the connection to the Samen Kwiek platform, providing insights into the changes in transaction frequency, asset specificity, and uncertainty resulting from the platform's implementation. The study contributes to the existing literature on collaborative business modeling, value capture, and transaction cost analysis, offering practical recommendations to optimize value capture and minimize transaction costs for Samen Kwiek and similar platforms. The findings are relevant for platform developers, service providers, and policymakers in the domain of preventive healthcare. In summary, this study sheds light on the factors influencing value capture and transaction costs in a platform-based ecosystem, providing valuable insights for stakeholders involved in the design, implementation, and management of digital platforms in the context of preventive healthcare.},
  howpublished = {https://essay.utwente.nl/95341/},
  langid = {english},
  file = {/Users/dkapitan/Zotero/storage/Y2YKQ8JB/Zegers - 2023 - How to capture maximum value through minimizing tr.pdf;/Users/dkapitan/Zotero/storage/SM9IAZZ5/95341.html}
}

@incollection{zemlin2024open,
  title = {Open {{Source}}, {{The Ubiquitous Software Innovation Building Block}}},
  booktitle = {The {{Oxford Handbook}} of {{Open Innovation}}},
  author = {Zemlin, James},
  editor = {Chesbrough, Henry and Radziwon, Agnieszka and Vanhaverbeke, Wim and West, Joel},
  year = {2024},
  month = feb,
  pages = {0},
  publisher = {Oxford University Press},
  doi = {10.1093/oxfordhb/9780192899798.013.44},
  urldate = {2024-02-29},
  abstract = {In less than two decades, open source software has come to dominate the technology landscape across a wide swathe of key software categories, including operating systems, machine learning, databases, web servers, and more. The open source innovation model has evolved to support a rapidly expanding ecosystem and body of practice supplanting traditional technology development, sales, marketing, and management practices. Open source is also increasingly sparking innovation and forming communities to tackle broad industry problems in diverse fields, including agriculture, public health, motion pictures, and telecommunications. Building on the foundational work of Henry Chesbrough, Eric von Hippel, and Yochai Benkler in Open Innovation, hobbyist technology innovation, and peer-based production, this chapter explores the rise to dominance of open source, the market disruption this emergence has created, and how open source is reshaping legacy business practices not only for early-stage innovation but also for later-stage innovation and collaboration, at scale.},
  isbn = {978-0-19-289979-8}
}

@inproceedings{zhao2021zonebased,
  title = {A {{Zone-Based Data Lake Architecture}} for {{IoT}}, {{Small}} and {{Big Data}}},
  booktitle = {25th {{International Database Engineering}} \& {{Applications Symposium}}},
  author = {Zhao, Yan and Megdiche, Imen and Ravat, Franck and Dang, Vincent-nam},
  year = {2021},
  month = jul,
  pages = {94--102},
  publisher = {ACM},
  address = {Montreal QC Canada},
  doi = {10.1145/3472163.3472185},
  urldate = {2024-03-27},
  isbn = {978-1-4503-8991-4},
  langid = {english},
  file = {/Users/dkapitan/Zotero/storage/W6I3EBDL/Zhao et al. - 2021 - A Zone-Based Data Lake Architecture for IoT, Small.pdf}
}