December 2020

The recommendations that follow represent a vision for evolving the current quality measurement ecosystem while maintaining its most effective elements. A few key themes recur.

• The importance of refining and developing quality measurement to help stakeholders drive toward health equity and address social determinants of health.

• The potential to reduce burden and improve care by moving to a digital quality measurement system that captures quality data during care delivery and provides results and decision support much more rapidly.

• The essential role of data validation to ensure accurate payments in value-based models.

Principles

Comparable. The ability to compare quality and value across settings and models of care (managed care, ACOs, fee-for-service, etc.) is fundamental. The burden and “noise” resulting from non-aligned measures that cannot be compared represents waste – in terms of time and money for all parties – and a lost opportunity to understand and prioritize what drives high-quality, person-centered care.

Meaningful. As we streamline the number of measures reported, how and what we measure must be determined with an eye toward higher quality, better outcomes, and more equitable results. This includes the ability to stratify measures based on race, ethnicity and language and capture information on social determinants of health that, in turn, inform the development of upstream solutions.

Valid and Reliable. Great gains have been made in the collection and sharing of healthcare data since the passage of the HITECH provisions in the 2009 stimulus bill. Still, billions of dollars in performance-based payments are made each year based on data that is inadequately validated or merely attested to. Strengthening standards and requirements for the validation of quality data and the platforms through which they flow will make the measurement and identification of high-value care more accurate and continuously improve the efficacy of future initiatives.

Actionable and Timely. HEDIS has enabled significant improvements in healthcare but it has been necessarily retrospective, yielding results months after care is provided. Shortening the feedback loop on measurement will greatly enhance the ability to drive quality improvement longitudinally and at the point of care. Outcome-Oriented. While process measures closely tied to outcomes – such as cancer screenings – remain extremely valuable, the system needs better, more relevant outcome measures to help differentiate quality. Among these should be patient-driven outcome measures based on individualized needs and goals, particularly for people with complex conditions.

Patient-Centered. Attempting to measure quality at the individual clinician level, however well-intentioned, often leads to a fragmented, incomplete view of a patient’s care. The federal government’s efforts to incentivize the move to system-based payment models (such as the Medicare Shared Savings Program and the Advanced Alternative Payment Model track in MIPS) acknowledge this reality. The Biden Administration should maintain and strengthen policies encouraging such models and pilot programs to drive patient-centered accountability for those practicing in a non-system environment.

Digital. As noted, the key to realizing many of the benefits described above is unleashing the transformative capabilities that the move to digital systems has demonstrated in other segments of the economy – from retail to transportation to entertainment. We commend CMS for its declaration that all quality measures will be reported digitally by 2030 but believe the process requires explicitly rewarding the move to digital through prudent investments and forward-looking digital measure policy.

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