CMS’ Roadmap for Switching to FHIR-Based Digital Quality Measures

Why It Matters

Modernizing the technical foundation improves interoperability, accelerates automated reporting, and enhances overall care quality across Medicare and Medicaid programs.

Key Takeaways

• CMS moving from eCQMs to FHIR‑based dQMs
• 70+ measures released for public comment now
• Goal: reduce provider reporting burden, increase interoperability
• QI‑Core, QM, DEQM guides standardize data representation
• MADiE tool streamlines measure authoring and testing

Pulse Analysis

For more than a decade, CMS has relied on electronic clinical quality measures (eCQMs) built on the Quality Data Model to track performance across Medicare and Medicaid. While eCQMs introduced automated reporting, their tight coupling to EHR data and limited data exchange have constrained cross‑system analytics and added reporting complexity for clinicians. Recognizing these gaps, CMS is pivoting to digital quality measures that leverage the Fast Healthcare Interoperability Resources (FHIR) standard, promising a more flexible, reusable, and real‑time data framework.

The transition hinges on a suite of FHIR‑based implementation guides—QI‑Core, Quality Measure (QM) IG, and Data Exchange for Quality Measures (DEQM) IG—that define consistent clinical vocabularies, measure logic, and exchange protocols. By aligning human‑readable specifications with computable resources, these guides enable seamless data sharing across hospitals, outpatient clinics, medical devices, and patient‑facing apps. CMS also introduced the Measure Authoring Development Integrated Environment (MADiE), a web‑based platform that automates authoring, testing, and publishing of both legacy eCQMs and new dQMs, dramatically shortening development cycles and reducing errors.

CMS has published draft dQM packages for 17 inpatient, 4 outpatient, and 49 clinician measures and opened a public comment window through Feb. 23, 2026. This early‑stage feedback loop gives providers, vendors, and health‑IT groups a chance to flag ambiguities, suggest data element refinements, and assess workflow impacts before full deployment. Successful adoption could lower reporting overhead, improve population‑health analytics, and set a national benchmark for interoperable quality measurement, positioning the United States to leverage emerging digital health data streams at scale. Stakeholders are encouraged to submit detailed use‑case scenarios to inform future revisions.

CMS’ Roadmap for Switching to FHIR-Based Digital Quality Measures

David Raths · Feb. 8, 2026

The Centers for Medicare & Medicaid Services (CMS) is moving steadily toward the use of FHIR‑based digital quality measures (dQMs). CMS believes dQMs will enable a more dynamic, interoperable, and comprehensive approach to quality measurement than the electronic clinical quality measures (eCQMs) currently in use.

As it seeks public feedback on draft dQM packages, CMS officials held a webinar in January to explain the expected transition.

One of the webinar speakers was Joel Andress, the digital quality measurement lead at CMS, who heads up efforts to develop and implement a strategy to convert CMS quality measurement to a digital format. The goals are to reduce reporting burden for care providers and promote data interoperability.

“We’re hoping to set expectations for upcoming changes in how quality measures are developed, implemented, and reported across our programs and give you an opportunity to actively participate in that transition,” Andress said.

He noted that digital quality measures enable alignment between clinical care, reporting requirements, and program accountability that have long been sought in CMS quality programs.

“Our belief is that by implementing digital quality measures, we’ll be able to support the long‑term sustainability of these programs and greater improvement in the quality of care in our provider systems,” Andress said.

Andress explained what it means that CMS programs are transitioning from traditional measures to FHIR‑based digital quality measures. These changes may include updated measure logic, new data requirements, and enhanced technical specifications, and are designed to improve measure validity, increase the interoperability of the data being collected, and support automated reporting within CMS’s programs.

“We are seeking to ensure that there is an alignment between human‑readable and computable specifications that we’ve developed in the FHIR standard, ensure that there’s a feasibility of collecting required data elements in EHR systems, and try to get a sense of what the potential impact on reporting workflows and provider burden would be given the changes to these measures,” he said.

The feedback period will give CMS an opportunity to obtain clear insight into the transition of digital quality measurement, equip stakeholders with the context needed to understand what CMS is changing about these measures and the presentation of information regarding them, and to enable meaningful participation in the development and implementation process.

These measures converted to FHIR will ultimately represent a subset of digital quality measures that will be a much more expansive category and incorporate other sources of data and reporting. While related, Andress explained, digital quality measures are distinct from the current program eCQMs and are built on a different data model and technical foundation.

The eCQMs have been used for many years across CMS Quality Reporting Programs. They’re based on the Quality Data Model (QDM), which is designed specifically for CMS use and primarily for reporting from electronic health records. The eCQMs have enabled automated reporting compared to manual abstraction, but are limited in their interoperability and are closely tied to EHR‑based data sources.

Digital quality measures, on the other hand, are built on the FHIR standard and use interoperable data. Designed to be modular, reusable, and scalable across programs and use cases, the measures can include data requirements that are not confined to a single system. Digital quality measures expand the concept of data sources to include medical devices, clinical systems, patient‑facing applications, and other digital health technologies beyond traditional EHRs.

Converting eCQMs to dQMs

Andress explained that “converting eCQMs to dQMs preserves existing measure intent while modernizing the technical foundation, and that positions CMS quality programs for greater interoperability, reduced reporting burden, and more comprehensive and timely quality insights.”

FHIR provides a comprehensive framework for implementing clinical quality measures and offers a standardized set of resources and operations that support the representation, sharing, and evaluation of clinical knowledge artifacts.

“Additionally, it’s not constrained simply to the quality measurement purpose, and this means that the data are interoperable for a variety of purposes, not simply within our reporting programs,” Andress said. “The framework enables standardization and interoperability by using consistent data formats and structures and facilitating seamless integration across the diverse healthcare systems.”

FHIR’s modular design and RESTful APIs support rapid implementation, scalability, and adaptability to evolving requirements. Data collected for the purpose of CMS’s program are reusable for different purposes, increasing the efficiency of data collection. FHIR also supports efficient handling of large data sets and enables population‑level analysis and reporting.

Currently, there are 157 resources in FHIR. Some of the common resources used with CMS digital quality measures include:

• Clinical module: allergy intolerance, condition (problems), procedure, and care plans resources (some may reference other resources such as service requests).

• Diagnostics module: observation and diagnostic report resources.

Andress explained that the QI‑Core Implementation Guide (IG) is a FHIR‑based implementation guide developed to standardize how clinical data are represented for quality measurement and improvement. It provides a bridge between clinical care data and digital quality measures, ensuring consistent and interoperable representation of clinical concepts needed for quality measurement, and supporting quality reporting programs, clinical decision support, and population health initiatives.

“In a nutshell, the QI‑Core IG is a foundational guide that defines how clinical data should be represented in FHIR so that quality measures can be accurate, interoperable, and implementable,” he said.

Other IGs key to the implementation of measures include:

• Quality Measure IG (QM IG) – defines how a measure is constructed.

• DEQM (Data Exchange for Quality Measures IG) – defines how to exchange digital quality measurement data between systems, i.e., how to report the measures to CMS.

Andress described a tool called MADiE (Measure Authoring Development Integrated Environment) that is designed for the creation, testing, and management of both eCQMs and digital quality measures.

“MADiE streamlines the development, testing, and management of quality measures to improve healthcare reporting outcomes. MADiE’s role is also to publish the artifacts that are there for you to assist you in the implementation of these measures,” he said. “So much of what you’ll be reviewing in the public comment beginning today comes from the MADiE system.”

With the dQM public comment period, CMS is publishing the dQM measure packages for those measures CMS has converted to the FHIR standard. “The publication of these packages containing these files that I’ve described includes what we believe to be an appropriate representation of the artifacts that would publish in future annual updates for those dQMs. So essentially we’re presenting to you what we think measure packages would look like once we implemented FHIR digital quality measurement reporting,” Andress said.

Andress concluded by saying that stakeholders now have a way to see how CMS has mapped out these measures, what they look like, and provide feedback.

“We also want to hear about any ambiguities in how we’ve presented the materials, whether or not something’s missing that would be important to include, or if something is presented in a way that’s difficult to use.”

The draft dQM packages are available through ONC JIRA tickets, including 17 hospital inpatient digital quality measures, four hospital outpatient digital quality measures, and 49 eligible clinician digital quality measures. Test case exports are provided for some of those measures, and public comments are open through Feb. 23, 2026.