Machine learning is a branch of artificial intelligence focused on building applications that learn from data and improve their accuracy over time without being programmed to do so. IBM Cloud Education (2020, July, 15). Machine learning. https://www.ibm.com/cloud/learn/machine-learning
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 may also be measure developers. 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. Adapted 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 evaluated concept and achieves the intended purpose (to measure quality). For example, the measure
- clearly identifies the evaluated concept (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)
Measured entities are the front-line clinicians and their organizations, including health information technology, collecting quality measurement data. Measured entities are the implementers of quality measures. The effect of quality measure data collection on clinician workflow can be negative. There may be effects on their payments, positive and negative, with respect to reporting and actual performance on quality measures. Because of these potential effects, measured entities should be involved in all aspects of the Measure Lifecycle.
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 Social Security Act (SSA) as amended by Section 3014 of the Patient Protection and Affordable Care Act.