We used Python 3.8 and R 4.2.1 for this analysis.
We used the same methods from fall and pressure ulcer papers to build the sample data for fall hospitalizations in 2016 and 2017 (the previous study period in the fall paper was for 2011 - 2015). We identified major injury fall hospitalizations from MedPAR data, and linked the claims to MDS assessments for residents who were discharged from nursing homes, admitted to the hospital within one day, and returned to the same nursing home within one day after hospital discharge.
Scripts used in this step were listed in the "fall" folder.
By linking MDS data and MBSF data, we created several nursing home-level variables that were used in the paper: the number of Medicare fee-for-service residents in nursing homes stratified by short stay and long stay as well as by White and Non-White, the percent of White residents, the percent of residents dually eligible for Medicare and Medicaid, the percent of residents with ADRD. We also aggregated ratings and quality measures from Nursing Home Care Compare (NHCC) data for nursng homes. Below are the scripts in this step.
| Script name | Input files (File source) | Output files |
|---|---|---|
| 0_create_nh_variables_mbsf.py | MDS and MBSF and MBSF Chronic Conditions from 2011 - 2017 | nh_medicare_res_count_shortlongstay.csv nh_medicare_res_count_shortlongstay_race.csv nh_variables_capser.csv |
| 0_medicare_count_adrd.py | MDS and MBSF and MBSF Chronic Conditions from 2011 - 2017 | nh_adrd.csv |
| 0_create_nhc_data.py | Ratings and quality measure data from NHCC website | nh_nhc_measures.csv |
This step combined MDS reporting data previously created for falls and pressure ulcers. Please see detailed descriptions and code in corresponding links. The script for this step is 1_merge_all_mds_item.py, and the output from this script was all_mds_items_data.csv.
This step created nursing home sample from CASPER and LTCfocus, linked MDS reporting data to nursing home characteristics, and transformed all nurisng home-year variables to nursing home variables. Below are the scripts in this step.
| Script name | Input files (File source) | Output files |
|---|---|---|
| 2_create_nh_sample_casper_ltcfocus.R | CASPER and LTCfocus data from 2011 - 2017 | casper_and_ltc_clean2.csv |
| 3_create_final_nh_sample.py | all_mds_items_data.csv casper_and_ltc_clean2.csv nh_nhc_measures.csv nh_medicare_res_count_shortlongstay.csv nh_medicare_res_count_shortlongstay_race.csv nh_variables_capser.csv forhp-eligible-zips.csv |
nh_characteristics_20221020.csv |
This script 4_create_exhibits.R used the final nurisng home sample data from last step and created all exhibits published in the paper.