Bulk-FHIR-Validation/README.md
2024-09-11 12:25:47 +02:00

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# Bulk FHIR validation
Dockerized Open Source environment for **bulk FHIR validation of FHIR resources**.
## Aggregation and presentation of bulk validation results
This bulk FHIR validation environment **aggregates/groups and presents validation results of bulk FHIR validation** of FHIR Search results.
![Bulk FHIR validation](bulk-fhir-validation.png)
## Based on open standards and powerfull and flexible Open Source Software
Therefore this validation environment uses following standards and Open Source Software by the Python Library [fhirvalidation.py](home/fhirvalidation.py):
- Loading FHIR resources to be validated by [FHIR search](https://www.hl7.org/fhir/search.html) (for documentation see section "Select resources to be validated by FHIR Search parameters" below)
- [FHIR validation](https://www.hl7.org/fhir/validation.html#op) by [HAPI FHIR Validator](https://hapifhir.io/hapi-fhir/docs/validation/introduction.html) configured by Docker environment variables
- Aggregation by [Python Pandas](https://pandas.pydata.org/docs/user_guide/index.html) dataframe
- Presentation of validation results in web UI by [Jupyter Lab](https://jupyterlab.readthedocs.io/en/latest/)
## Architecture
![Software architecture](bulk-fhir-validator.drawio.png)
## Installation and Configuration
### Setup FHIR Packages
Download the FHIR NPM Packages of the [German MII Core Dataset modules](https://www.medizininformatik-initiative.de/de/uebersicht-ueber-versionen-der-kerndatensatz-module) (Kerndatensatz der Medizininformatik Initiative) to the directory `fhir-packages`.
E.g. by running [download-packages.sh](download-packages.sh):
``
bash download-packages.sh
``
If you want to use other FHIR packages, download the NPM packages to the fhir-packages directory and set them up by the environment variables of the HAPI validation service.
The environment variable names is derived from config section `implementationguides` in HAPIs [application.yaml](https://github.com/hapifhir/hapi-fhir-jpaserver-starter/blob/master/src/main/resources/application.yaml)
### Create config file
Copy .env.skeleton to .env (so .env which will contain your credentials will be excluded from the git repo by .gitignore):
`cp .env.example .env`
### Setup your FHIR server parameters
Edit [.env](.env.example) and set up custom parameters like the URL for your FHIR Server.
### Setup initial password for Jupyter Lab UI
Set a custom initial token in variable `JUPYTER_TOKEN` in `.env`
### Start validation environment
Start the validation environment by
``
docker compose up -d
``
## Usage
### Web UI
Access the [web user interface of Jupyter Lab](https://jupyterlab.readthedocs.io/en/latest/) on the configured (default: 80) port:
http://yourserver/
#### Login
Login with the initial password / token you configured in .env
#### Start validation
Now you can start the validation and aggregation of validation results.
Therefore run the Jupyter Notebook [fhir-validation.ipynb](home/fhir-validation.ipynb).
#### Navigate validation results
You can navigate the validation results by "Table of Content" of Jupyter Lab. Therefore switch the left navigation bar from "File browser" to "Table of Contents".
#### User documentation
The further user documentation is embedded in the Jupyter Notebook:
The different outputs are described in markdown cells and used parameters are described in the code cells.
### Select resources to be validated by FHIR Search parameters
You can select/filter the resources to be validated by [FHIR search](https://www.hl7.org/fhir/search.html) parameters.
For filter options you can set `search_parameters`, see [FHIR search common parameters for all resource types](https://www.hl7.org/fhir/search.html#standard), as well as additional FHIR search parameters for certain resource types like [Patient](https://www.hl7.org/fhir/patient.html#search), [Condition](https://www.hl7.org/fhir/condition.html#search), [Observation](https://www.hl7.org/fhir/observation.html#search), ...
### Python library
If you dont want to use Jupyter Lab as a user interface (e.g. if you want to generate markdown for CI/CD reports), you can use the Python library [fhirvalidation.py](home/fhirvalidation.py) returning a [pandas](https://pandas.pydata.org/docs/user_guide/index.html) dataframe independent from Jupyter Lab.
In the Jupyter Notebook, you can find documentation on how to use the library, including example with code snippets.