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Personalized Patient Experience with Digital Front Door

This repository contains code examples and utilities for implementing personalized experiences for healthcare members through a digital front door solution, leveraging AWS services like Amazon Bedrock and OpenSearch Serverless.

Overview

The code demonstrates two approaches to personalize the digital front door experience:

  1. Leveraging a Vector Database: This approach uses OpenSearch Serverless as a vector database to store and retrieve personalized information based on a member's plan details.

  2. Leveraging Knowledge Bases from Amazon Bedrock: This approach utilizes Amazon Bedrock's Knowledge Bases to store and retrieve personalized information based on metadata filters.

Prerequisites

Before running the code, ensure that you have the following prerequisites:

  • AWS account
  • Python 3.7 or later
  • Required Python packages (e.g., boto3, pandas, etc.)

Installation

  1. Clone the repository:
git clone https://github.com/aws-samples/aws-patient-digital-front-door.git
  1. Install the required Python packages:
pip install -r requirements.txt

Architecture

Architecture

Contributing

Contributions are welcome! If you find any issues or have suggestions for improvements, please open an issue or submit a pull request.

License

This project is licensed under the MIT License.

Acknowledgments