NCQA to Pilot HEDIS Measures Using FHIR Data Model

July 23, 2020
Later this year the National Committee for Quality Assurance will release a small number of FHIR-CQL HEDIS measures for trial use

As the National Committee for Quality Assurance (NCQA) heads down a path that includes more digital quality measures, the organization also is getting ready to begin piloting FHIR data model-based HEDIS measures in 2020.

For definitional purposes, digital quality measures will pull data from a broad array of sources, including EHRs, registries, HIEs, claims, and patient experience surveys, whereas electronic clinical quality measures data primarily pulls data from EHRs. NCQA is shifting to digital quality measures because it will make it easier to transfer measures into IT systems; reduce interpretation, recoding, and human error; and ease use across the care continuum.

Digital quality measures are being designed using the Clinical Quality Language (CQL), which is a data model-agnostic expression language. It allows authors to build efficient clinical quality measures (eCQMs) that are both machine- and human-readable. It simplifies artifacts to improve the ability to implement and share. Soon CQL will be combined with FHIR.

Along with standards organization HL7, NCQA hosted a Digital Quality Summit July 22 and 23, designed to foster engagement and collaboration around advances in digital quality measurement.

Speaking at the virtual event, Emily Morden, M.S.W., director of electronic measurement strategy in the Performance Measurement Department at NCQA, explained why the organization is switching data models. “We hope it is going to lead to reduced provider burden by easing data collection efforts, and we also see it as an opportunity to have other quality measurement use cases,” she said. “For example, FHIR provides more resources that the Quality Data Model, which will expand the utility of use cases for any quality measures that are specified. We also want to maintain alignment with other key stakeholders, and we know that others are also looking to move toward FHIR for their measures and reporting programs."

As a first step, later this year NCQA is going to be releasing a small number of FHIR-CQL HEDIS measures for trial use. "This will be an opportunity for folks to be able to see what our digital quality measures look like using the FHIR data model and get that preview of what they can expect for the future," Morden said. "We are planning to release our first set of FHIR-CQL measures to be used in year 2022, which gets reported for HEDIS in June 2023.” NCQA will be organizing FHIR pilots starting later this year.

In a blog post on the NCQA website, consultant Michael Klotz provided a clear explanation of the new direction:

As FHIR was being developed (and would quickly become the de facto standard for interoperability), the primary standard for dQMs had two components: 

1. Quality Data Model—QDM—a standard and machine-readable way of defining data elements and structure for data to be consumed and processed by CQL. 

2. Clinical Quality Language—CQL—a standard and authoring language that is both a human- and machine-readable way of declaring all the quality rules for a given measure. 

Because both FHIR and QDM-CQL already share the same underlying (modern, widely adopted) technologies, it only makes sense to merge data definitions. And because both were developed under the HL7 umbrella, a smooth transition from QDM-CQL to FHIR-CQL is ensured. ….If the trials go as expected, there will be a transition from QDM-CQL to FHIR-CQL in relatively short order. In addition, we will likely see additional measures (traditional measures, ECDS) implemented in FHIR-CQL. The ultimate goal is to have all measures in one dQM standard (FHIR-CQL being the obvious candidate), which will not only simplify measure definitions and software development, but will also significantly further automation and streamlining of data collection and measure reporting. 

While it might be premature to claim that FHIR-CQL can be implemented for all measures, we can say that it will blaze a trail—especially given that clinical data is becoming more structured, standardized and universally accessible, thanks to interoperability initiatives already underway. 

NCQA also has launched a Digital Measurement Community, a new interactive platform for stakeholders engaged in the development and implementation of digital quality measures. To sign up, visit: