The ONC Certification (g)(10) Standardized API Test Kit is a testing tool for Health IT systems seeking to meet the requirements of the ONC Standardized API for Patient and Population Services criterion § 170.315(g)(10) in the ONC Certification Program.
The (g)(10) Standardized API Test Kit behaves like an API consumer, making a series of HTTP requests that mimic a real world client to ensure that the API supports an approved version of each of the required standards:
- Health Level 7 (HL7®) Fast Healthcare Interoperability Resources (FHIR®) (v4.0.1)
- US Core Implementation Guide (v3.1.1, v4.0.0, v6.1.0, or v7.0.0)
- SMART Application Launch Framework Implementation Guide Release (v1.0.0, v2.0.0, or v2.2.0)
- HL7 FHIR Bulk Data Access (Flat FHIR) (v1.0.1, or v2.0.0)
Please note that US Core Implementation Guide v.7.0.0 should only be used with SMART Application Launch Guide v2.0.0 or above due to granular scope support requirements.
This test kit is open source and freely available for use or adoption by the health IT community including EHR vendors, health app developers, and testing labs. It is an approved test method for the § 170.315(g)(10) certification criterion in the EHR Certification program by the Office of the National Coordinator for Health IT (ONC).
The (g)(10) Standarized API Test Kit is built using the Inferno Framework. The Inferno Framework is designed for reuse and aims to make it easier to build test kits for any FHIR-based data exchange.
ONC hosts a public instance of this test kit that developers and testers are welcome to use. However, users are encouraged to download and run this tool locally to allow testing within private networks and to avoid being affected by downtime of this shared resource. Please see the Local Installation Instructions section below for more information.
ONC hosts a (g)(10) reference server that can be used to orient new users on these tests. The (g)(10) Standardized API Test Kit Walkthrough provides step-by-step instructions for running these tests against the reference server. This reference server is not a complete implementation and cannot be used for production use.
Please report any issues with this set of tests in the GitHub Issues section of this repository. Common questions and answers are documented in the (g)(10) Test Kit Frequently Asked Questions.
- Download an official release
- run
setup.sh - run
run.sh - navigate to
http://localhost
The default configuration of this test kit uses SQLite for data persistence and is optimized for running on a local machine with a single user. For installations on shared servers that may have multiple tests running simultaniously, please configure the installation to use PostgreSQL to ensure stability in this type of environment.
In order to validate terminologies, Inferno must be loaded with files generated from the Unified Medical Language System (UMLS). The UMLS is distributed by the National Library of Medicine (NLM) and requires an account to access.
Inferno provides some rake tasks which may make this process easier, as well as a Dockerfile and docker-compose file that will create the validators in a self-contained environment.
Prerequisites:
- A UMLS account
- A working Docker toolchain, which has been assigned at least 10GB of RAM (The
Metathesaurus step requires 8GB of RAM for the Java process)
- Note: the Docker terminology process will not run unless Docker has access to at least 10GB of RAM.
- At least 40 GB of free disk space on the Host OS, for
downloading/unzipping/processing the terminology files.
- Note: this space needs to be allocated on the host because Docker maps these files through to the Host, to allow for building in the dedicated terminology container.
- A copy of the Inferno repository, which contains the required Docker and Ruby files
- Run
setup.shto initialize Inferno's database
Once you have a UMLS account, you will have to add your UMLS API key to a file
named .env at the root of the inferno project. This API key is used to
authenticate the user to download the UMLS zip files. To find your UMLS API key,
sign into the UTS homepage, click on My Profile in the top right, and copy the API KEY value from the UMLS Licensee Profile.
The relevant entries in the .env file should look like this (replacing
your_api_key with your UMLS API key):
UMLS_API_KEY=your_api_key
CLEANUP=trueNote that anything after the equals sign in .env will be considered part of
the variable, so don't wrap your API key in quotation marks.
Optionally: you can add a second environment variable, named CLEANUP and set
to true, to that same file. This tells the build system to delete the "build
files"--everything except for the finished databases--after the build.
Once that file exists, you can run the terminology creation task by using the following command:
docker compose -f terminology_compose.yml up --buildThis will run the terminology creation steps in order. These tasks may take
several hours. If the creation task is cancelled in progress and restarted, it
will restart after the last completed step. Intermediate files are saved to
tmp/terminology in the Inferno repository that the Docker Compose job is run
from, and the validators are saved to resources/terminology/validators/bloom,
where Inferno can use them for validation.
Once the terminology building is done, you should remove your UMLS API key from the system.
Optionally, the files and folders in tmp/terminology/ can be deleted after
terminology building to free up space, as they are several GB in size. If you
intend to re-run the terminology builder, these files can be left to speed up
building in the future, since the builder will be able to skip the initial
download/preprocessing steps.
The following rake task will check that the built terminology contains the expected number of codes for each system:
bundle exec rake terminology:check_built_terminologyYou can use the following rake command to spot check the validators to make
sure they are installed correctly:
bundle exec rake "terminology:check_code[91935009,http://snomed.info/sct, http://hl7.org/fhir/us/core/ValueSet/us-core-allergy-substance]"Should return:
X http://snomed.info/sct|91935009 is not in http://hl7.org/fhir/us/core/ValueSet/us-core-allergy-substance
And
bundle exec rake "terminology:check_code[91935009,http://snomed.info/sct]"Should return:
✓ http://snomed.info/sct|91935009 is in http://snomed.info/sct
Running instances of Inferno can be configured to exclude terminology validation for codes based on applicable categories of additional restrictions, as defined by the UMLS license agreement.
By default, Inferno will not restrict validation of codes. To configure an
instance of Inferno to exclude certain CodeSystems for validation, rename the
resources/terminology/terminology_config.yml.example to
terminology_config.yml, and update the file based on the example content.
Inferno will provide an informational message on the landing page that describes
which CodeSystems will not be validated in this running instance based on this
configuration file. If Inferno tests receive a code from an excluded
CodeSystem, a warning indicating that Inferno cannot validate the code will be
provided along with the test result.
TODO: Update this section
If this Docker-based method does not work based on your architecture, manual setup and creation of the terminology validators is documented on this wiki page
Some material in the UMLS Metathesaurus is from copyrighted sources of the respective copyright holders. Users of the UMLS Metathesaurus are solely responsible for compliance with any copyright, patent or trademark restrictions and are referred to the copyright, patent or trademark notices appearing in the original sources, all of which are hereby incorporated by reference.
Bodenreider O. The Unified Medical Language System (UMLS): integrating biomedical terminology.
Nucleic Acids Res. 2004 Jan 1;32(Database issue):D267-70. doi: 10.1093/nar/gkh061.
PubMed PMID: 14681409; PubMed Central PMCID: PMC308795.
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