This section provides an overview of the types of testing needed to assess measure evaluation criteria and outlines the process for development, implementation, and reporting of test plans, results, and associated artifacts. Information in this section is not meant to be prescriptive or exhaustive. Measure developers can use other testing approaches that employ appropriate methods and rationales. Measure developers should always select testing that is appropriate for the measure under development and provide empirical evidence for the importance to measure and report, feasibility, scientific acceptability, and usability and use.
Measure testing is an iterative process conducted concurrently with measure specification. Iterative testing provides measure developers an opportunity to refine draft specifications before finalization; augment or reevaluate earlier judgments about the measure’s importance; and assess feasibility, usability, and scientific acceptability of the measure.
Measure testing enables a measure developer to assess suitability of the quality measure’s technical specifications and acquire empirical evidence to help assess strengths and weaknesses of a measure with respect to the CMS consensus-based entity Measure Evaluation Criteria and Guidance for Evaluating Measures for Endorsement. To evaluate a measure, the measure developer should use information gathered through measure testing in conjunction with expert judgment. Measure testing refers to evaluating the draft specifications of quality measures, including components of the quality measures, such as the data elements, instruments, and performance score.
Testing and Evaluation for Special Measures
Special types of measures may require the measure developer to assess different measure aspects. For example, while measure developers assess all measures for feasibility, data element feasibility is a major focus in testing and evaluating electronic clinical quality measures (eCQMs). To assist in assessing an eCQM’s feasibility, the measure developer needs to include the eCQM Feasibility Scorecard, not only as part of the testing plan, but also during feasibility testing as changes happen. For the measure testing summary related to an eCQM, documentation must show
- Evidence of testing with at least two different electronic health records
- Quality Data Model data elements and the feasibility ratings of those elements
Because composite measures include component measures, there are additional considerations when testing and evaluating composite measures. For more information on testing and evaluating special types of measures, refer to the supplemental materials that describe special measures: