Category: healthcare

Since announcing CQL Tests UI, the application has continued to receive enhancements that add the ability to execute new test runs yourself using the official CQFramework-family of CQL tests.

What’s New: The Runner Integration

The upcoming release introduces a complete CQL Test Runner integration that will allow users to execute CQL compliance tests directly from the web interface. No more switching between tools or managing configuration files manually.

Key Features Added

Live Test Execution: The new runner component will let you configure and execute the separately-running CQL test runner service against any CQL-capable FHIR server with a few clicks. Tests will run asynchronously in the background via the test runner, and results will be reported via the UI where they can be seamlessly loaded into the existing viewer.

Flexible Configuration: The interface provides a user-friendly way to configure FHIR server endpoints, build settings, and test parameters. For power users, there will be a full JSON editor with syntax highlighting.

Separate Deployment: The CQL Test Runner itself will operate as a separate service that needs to be deployed independently. It will be released as a Docker container.

Results Integration: Once tests complete, you’ll be able to immediately view results in the existing results viewer or download them as JSON. The integration will be seamless – test results will flow directly into the visualization tools you’re already familiar with.

Looking Forward

As the project continues to evolve, I’d personally like to see CQL Tests UI grow into an even more full-featured CQL authoring environment. There is exciting potential to combine or align with efforts from the CDS Connect Authoring Tool Community Edition, bringing together the best of test execution and authoring capabilities in a single, user-friendly interface.

Please share your thoughts with me via the GitHub repository, the FHIR Zulip community, or during the HL7 CQI and HL7 CDS working group calls.

I’m pleased to announce the release of CQL Tests UI, a web application for viewing and analyzing Clinical Quality Language (CQL) engine test results generated by the CQL Tests Runner. I’ve contributed CQL Tests UI to the cqframework family of tools under the Apache 2.0 license following debut at the September, 2025 HL7 Connectathon.

What is CQL Tests UI?

CQL Tests UI is an intuitive web application that provides an interface for visualizing the results of CQL engine compliance tests. Whether you’re working on clinical decision support rules, quality measures, or other CQL-based artifacts, this tool helps you quickly identify engine issues and compare results across different CQL execution implementation environments.

Key Features

Cross-Engine Comparison Dashboard

The dashboard provides a high-level dashboard summarizing test results across engines, allowing for broad-stroke summarization of correct CQL engine functionality across systems.

Detailed Result Viewer

The results detail viewer zooms in on a specific test run. This feature allows you to examine expected and actual output of individual test cases and understand failures.

Flexible Data Loading

The application supports multiple ways to load your test data, making it easy to integrate into existing workflows.

Documentation and Deep-Linking

Built-in documentation and deep-linking support make it easy to share specific test results and collaborate with team members.

References

• GitHub Repository
• Issues and Bug Reports
• Digital Quality Implementers Community (DQIC): A collaborative consensus-based effort to develop, advance, and standardize tools and platforms that make digital quality measurement possible, with initial focus on evolving CQL engines.
• HL7 Clinical Quality Information Workgroup: The HL7 workgroup responsible for developing and maintaining standards for clinical quality information, including CQL and related specifications.

As part of my work at Arizona State University, I’ve been developing the technology stack for the Substance Use Health Records Sharing (SHARES) program. This initiative aims to transform how sensitive health data for substance use disorders (SUD) are managed and shared across healthcare systems. At a personal technical level, my goal is to provide a set of flexible developer libraries, pre-canned API services, and exemplar web UI applications for all U.S. entities to comply with 42 CFR part 2 using FHIR.

While management of patient consent directives has its own set of challenges, such as those being addressed by the FAST Consent Management Implementation Guide, I’m more interested in the runtime enforcement of patient data sharing elections between organizations. Consent enforcement is an incredibly challenging area of healthcare interoperability wrought with legal and clinicotechnical quandaries.

SHARES has been on a publishing spree, and I’m proud to.. share.. that FHIR Granular Sensitive Data Segmentation has been published in Applied Clinical Informatics (ACI). The referenced data labeling approach to information sensitivity classification is done in compliance with the FHIR DS4P implementation guide and heavily influenced by the ONC LEAP Computable Consent program. While we didn’t reuse LEAP’s Java and JavaScript code as we wanted SHARES to be entirely done in native TypeScript, we still retain some compatibility with LEAP’s CDS Hooks-based FHIR data labeling service using a modified version of their schema. SHARES has since moved on, however, to supporting numerous other means of integration for security label-based data segmentation.

Since this manuscript was drafted, we’ve been hard at working rearchitecting the technology platform for scale, plugability of classification engines, and integration methodology. We also recently released v1 of a visual Consent Simulator that will be a focal point of upcoming technical iterations.

I’m particularly excited for the next few technical phases that will use the new pluggable architecture to provide alternative means of data segmentation. More on that in future publications. 🙂

For more information on the SHARES program, visit https://www.asushares.com .