The Meaningful Measures Framework is the Centers for Medicare & Medicaid Services's initiative which identifies the highest priorities for quality measurement and improvement. It involves only assessing core issues that are the most critical to providing high-quality care and improving individual outcomes. The Meaningful Measure Areas serve as the connectors between CMS goals and individual measures/initiatives that demonstrate how high-quality outcomes for CMS beneficiaries are being achieved.
A measure developer is an individual or organization responsible for the development, implementation, and maintenance of a measure. Measure developers create, edit, and submit measures for consideration by CMS to include in programs. CMS encourages developers to use the Blueprint as a guide in creating their measures and to collaborate with other measure developers to share best practices/new learnings freely e.g., CMS measure development contractor, hospital system, medical association, or federal health agency. Adapted from the CMS Measures Management System (MMS) Measure Developers webpage.
The measure score is the numeric result that is computed by applying the measure specifications and scoring algorithm. The computed measure score represents an aggregation of all appropriate patient-level data (for example, proportion of patients who died, average lab value attained) for the entity being measured (hospital, health plan, home health agency, clinician, etc.). The measure specifications designate the entity that is being measured and to whom the measure score applies.
A measure steward is an individual or organization that owns a measure and is responsible for maintaining the measure. Measure stewards are often the same as measure developers, but not always. Measure stewards are also the ongoing point of contact for people interested in a given measure e.g., medical specialty society or federal health agency. Retrieved from the CMS MMS Blueprint.
Measure testing is empirical analysis to demonstrate the reliability and validity of a measure as specified. It includes analysis of issues that pose threats to the validity of conclusions about quality of care such as exclusions, risk adjustment/stratification for outcome and resource use measures, methods to identify differences in performance, and comparability of data sources/methods.
Measure validity is when the measure accurately represents the concept being evaluated and achieves the purpose for which it is intended (to measure quality). See also Data element validity. For example, the measure
- Cleary identifies the concept being evaluated (face validity)
- Includes all necessary data elements, codes, and tables to detect a positive occurrence when one exists (construct validity)
- Includes all necessary data sources to detect a positive occurrence when one exists (construct validity)
The Measures under Consideration (MUC) is a list of quality and efficiency measures the Department of Health & Human Services is considering adopting, through the federal rulemaking process, for use in the Medicare program. The MUC list is made publicly available by December first each year for categories of measures that are described in section 1890(b) (7) (B) (i) (I) of the Affordable Care Act.