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Mock implementation of a server that provides clinical guideline recommendations in CPG-on-EBMonFHIR

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CODEX-CELIDA/recommendation-server

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CELIDA Recommendation Server

This is a mock recommendation server for the CELIDA project, serving the latest CELIDA recommendations from github. The only implemented FHIR search parameter is URL for any resource type.

On startup, the server downloads the latest CELIDA recommendations from https://github.com/CODEX-CEDLIA/celida-recommendations and serves them from memory at the FHIR endpoint /fhir.

This recommendation server can be used as input to the execution engine.

The docker image is available at https://hub.docker.com/repository/docker/glichtner/celida-recommendation-server/.

Usage

Run with docker

  1. Pull image from docker hub

    docker pull glichtner/celida-recommendation-server:latest
  2. Run container with specified environment variables

    docker run \
       -e "GH_REPOSITORY=https://github.com/CODEX-CELIDA/celida-recommendations" \
       --name celida-recommendation-server \
       -dp 8000:80 \
       glichtner/celida-recommendation-server

Build image yourself

  1. Clone this repository

  2. Build image:

     docker build -t celida/recommendation-server .
  3. Run container:

    docker run --env-file celida.env -dp 8000:80 celida/recommendation-server

Querying

Get all available versions of the fhir package:

curl "http://localhost:8000/fhir/version-history"

Query the server:

curl "http://localhost:8000/{fhir-resource-type}?url={url}"

For example:

curl "http://localhost:8000/fhir/PlanDefinition?url=https://www.netzwerk-universitaetsmedizin.de/fhir/codex-celida/guideline/covid19-inpatient-therapy/intervention-plan/peep-fio2-point4"

Contributing

We welcome contributions to this repository! If you have any suggestions or bug reports, please open an issue or a pull request.

Contact

For more information about the CODEX-CELIDA project, please visit https://github.com/CODEX-CELIDA.

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Mock implementation of a server that provides clinical guideline recommendations in CPG-on-EBMonFHIR

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