Introduction

This project provides a group of Docker services which periodically apply computer interpretable recommendations such as those defined in the CELIDA project to patient data in an OMOP formatted databased. The assumed overall process consists of the following actions/actors:

1. A component outside the scope of this project acts as a source of patient data and updates the OMOP-formatted section of the databse with new records. TODO either in real-time or on a regular basis.

2. In response to some trigger, the execution-engine service of this project scans the database for records to which the defined recommendations are applicable and creates suitable output records in a different section of the database. The trigger can be either:

   1. The database scan of the execution-engine is started on a regular basis, such as every five minutes.

   2. The data source component mentioned above or some other component notifies the execution-engine via an HTTP request of new records in the database.

3. A user-interface component retrieves (TODO on the fly or on a regular basis) the created records and presents them to users.

The database itself, the patient data source component and the user-interface component are outside of the scope of this project and must be set up separately.

Usage

1. Adapt database connectivity settings in docker-compose.yml

2. Start the services with docker-compose up

3. Trigger recommendation processing with the equivalent of curl -d '' http://localhost:12345

4. Retrieve recommentation results from the result_interval and execution_run tables of the configured result schema of the database (typically celida)