Quality Measurement: Technical Specifications and Key Development Considerations.

Abstract

In the United States, payers of health care and home and community-based services, such as the Centers for Medicare & Medicaid Services, have implemented various quality programs as a lever for improving the quality of services. A key component of any quality program is the set of quality measures adopted for use in the program. Quality measure results are calculated at regular intervals for each accountable entity (eg, organization) and can be shared with the respective organization in confidential feedback reports, displayed on websites (public reporting), and used in pay-for-performance programs to encourage providers to improve the quality of services. In this special communication, we focus on quality outcome measures, describing quality measure design options using the 5 core elements of a fully specified outcome, which have been defined in reporting guidelines for clinical trial protocols (Standard Protocol Items: Recommendations for Interventional Trials [SPIRIT]-Outcomes 2022 Extension), and clinical trial reports (CONsolidated Standards Of Reporting Trials [CONSORT]-Outcomes 2022 Extension). Element 1 of a measure is the domain or subdomain (the concept to be measured), element 2 is the specific measurement items or instrument, element 3 is the specific metric used to characterize participants' results (eg, end value, change from baseline, or time to event), element 4 is the method of aggregation (eg, mean for continuous data, proportion for categorical data, or risk-adjustment approach), and element 5 is the time point of the follow-up measurements. We explain risk adjustment for quality measures, which is used to adjust for case-mix differences across providers. We describe considerations for selecting quality measure risk factors, which can be used as covariates in a regression model, stratification variables, or exclusion criteria. Finally, we describe quality measure endorsement standards and future directions for quality measurement.