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dQMs - Digital Quality Measures

​​The Centers for Medicare & Medicaid Services (CMS) has set the goal of advancing quality measurement by transitioning all quality measures used in its reporting programs to digital quality measures (dQMs). CMS has developed a dQM Strategic Roadmap to outline the strategy activities required to transition to digital measurement.

Advancements in the interoperability of health care data and requirements from CMS and the Office of the National Coordinator for Health Information Technology (ONC) have created an opportunity to modernize CMS’s quality measurement systems. The ONC 21st Century Cures Act final rule requires health information technology (IT) developers to update their certified health IT to support Fast Healthcare Interoperability Resources (FHIR®) Release 4 and specific data standards. Aligning technology requirements for health care providers, payers, and health IT developers allows for advancement of an interoperable health IT infrastructure that ensures providers and patients have access to health data when and where it is needed.

CMS has outlined four domains to enable transformation of the quality measurement enterprise:

  • improve data quality
  • advance technology
  • optimize data aggregation
  • enable alignment of data, tools, and measures

For each of these four domains, CMS will evolve technical components, leverage policymaking, and engage stakeholders to improve patient care and support the transition to digital quality measurement over the coming years. This figure depicts the four key foci to advance digital quality measurement: improve data quality, advance technology, optimize data aggregation, and enable alignment of data, tools, and measures.

BP Overview


dQM Strategic Roadmap DocumentationPublished
FY 2022 Inpatient Prospective Payment System (IPPS)/Long-Term Care Hospital (LTCH) Prospective Payment System (PPS) final rule: Advancing to Digital Quality Measurement and the Use of Fast Healthcare Interoperability Resources (FHIR) in Hospital Quality Programs—Request for InformationAugust 2021
CY 2022 Physician Fee Schedule final rule: Advancing to Digital Quality Measurement and the Use of Fast Healthcare Interoperability Resources (FHIR) in Physician Quality Programs—Request for InformationNovember 2021
FY 2023 Inpatient Prospective Payment System (IPPS)/Long-Term Care Hospital (LTCH) Prospective Payment System (PPS) final rule: Continuing to Advance to Digital Quality Measurement and the Use of Fast Healthcare Interoperability Resources (FHIR) in Hospital Quality Programs —Request for InformationAugust 2022
dQM Strategic RoadmapApril 2022
dQM Strategic Roadmap Executive Summary Slide DeckApril 2022

​Digital Quality Measurement in a Learning Health System

Data standardization and interoperability support digital quality measurement. In digital quality measurement, the data used are digital, standardized, and a seamless outgrowth of data generated from routine workflows. Data sharing is standards-based to maximize interoperability, minimize burden, and facilitate the development and use of common tooling across use cases. This approach supports data analysis, rapid-cycle feedback, and quality measurement that are aligned for continuous improvement in patient-centered care. As interoperability standards and technology evolve, quality information could become available in near real-time, aiding in rapid improvement to patient care.

Once digital data can be captured, validated, shared, and merged for analysis, CMS will be poised to contribute to the promise of a learning health system that supports improved quality of patient care. In a learning health system, data are leveraged to inform multiple use cases, including quality measurement, improvement, and public health. The graphic shows the data cycle includes

  • surveillance activities to derive evidence from the data
  • translating evidence to clinical guidelines and clinical decision support
  • using data and guidelines to transform clinical care
  • conducting quality improvement activities
  • interpreting and applying the data to support measurement and analytics
  • reporting out results based on data

These actions are bi-directional and will lead to improved patient outcomes and the delivery of high-quality care for patients. CMS will continue to explore avenues for leveraging interoperable tools that facilitate impactful digital data and information sharing.

Learning Health Systems

CMS Digital Quality Measures

CMS defines digital quality measures (dQMs) as quality measures that use standardized, digital data from one or more sources of health information that are captured and exchanged via interoperable systems; apply quality measure specifications that are standards-based and use code packages; and are computable in an integrated environment without additional effort. The set of solutions for dQMs enables querying the data needed from standards-based application programming interfaces (APIs) (such as Fast Healthcare Interoperability Resources [FHIR®] APIs), calculating the measure score, and generating outputs necessary for quality reporting, that also support quality improvement efforts. dQMs improve patient care and experiences by ensuring patient and provider access to necessary information, improving the quality of care, the health of populations, and reducing costs due to the rapid-cycle nature of digital health data and dQM calculation.

The next graphic visualizes digital quality measures and how they can contribute to a learning health system. Structured digital health data are the building blocks (i.e., Lego®) for quality measures. In accordance with the dQM definition, the provenance of this data can be from one or more sources, which must be cleaned and validated for use. Standardized data exchanged via FHIR can be aggregated and used to calculate the specified quality measure (i.e., Lego house) providing insights to the health care ecosystem (i.e., Lego neighborhood).

dQM Definition HS

Digital Data Sources

As depicted in the graphic, some examples of digital data sources for dQMs are

  • administrative systems
  • electronically submitted clinical or social needs assessments
  • electronic health records (EHRs)
  • laboratory systems
  • prescription drug monitoring programs
  • instruments (for example, medical devices and wearables)
  • patient portals or applications (for example, for collection of patient-generated health data such as home blood pressure monitoring or patient-reported health data)
  • health information exchanges (HIEs)
  • clinical registries

dQM Definition

The FHIR Standard for CMS Digital Quality Measures

Electronic clinical quality measures (eCQMs), which typically use EHR data, may be refined or repackaged to better fit within the dQM umbrella. Operationally, the first step in CMS’s transition to dQM is to transition current CMS Quality Data Model (QDM)-eCQMs to CMS FHIR eCQMs. FHIR eCQM reporting will leverage standardized data and the FHIR model. It can serve as a model for how future digital reporting can occur to ultimately improve patient experience and quality of care. By revisiting existing value sets, data standards, measure logic and specifications and shifting specifications to the FHIR standard, CMS will pave the way for additional structuring of future, broader digital-based quality measures.

dQM Reference BriefsPublished date
Digital Quality Measurement & eCQMsApril 2023
Leveraging Data Standardization for Digital Quality MeasuresApril 2023

Introduction to Digital Quality Measures

Digital Quality Measurement Strategic Roadmap

Last Updated: Sep 07, 2023