Glossary

Face validity is the extent to which a test appears to cover the concept it purports to measure “at face value.” It is a subjective assessment by experts of whether the measure reflects the quality of care (e.g., whether the proportion of patients with blood pressure < 140/90 is a marker of quality.)

FHIR is a Health Level Seven International® (HL7) standard for exchanging health care information electronically. Health information technology implementers can use FHIR as a stand-alone data exchange standard but can also use in partnership with existing widely used standards. Health Level Seven International. (n.d.). FHIR overview. Retrieved November 1, 2023, from https://www.hl7.org/fhir/overview.html

Feasibility criteria is the extent to which the specifications, including measure logic, require data that are readily available or easily captured without undue burden and implemented for performance measurement.

Fisher's Exact Test is used to determine whether or not there is a significant association between two categorical variables. Zach. (2020, April 27). Fisher's Exact Test: Definition, Formula, and Example. Statology. Retrieved November 16, 2023, from https://www.statology.org/fishers-exact-test

The Friedman Test is a non-parametric test used to determine whether or not there is a statistically significant difference between the means of three or more groups in which the same subjects show up in each group. Zach. (2020, May 4). Friedman test: Definition, formula, and example. Statology. Retrieved November 27, 2023, from https://www.statology.org/friedman-test/

To meet these selection criteria, the measure developer must complete  testing of the measure. This means the measure developer has completed 

• Person/encounter-level (data element-level) reliability and validity testing, when appropriate, for each critical data element and the measure specifications do not need changes based on the results. Testing may be empiric or reference external or previous testing (e.g., established data element library such as the CMS Data Element Library (DEL) or Data Element Repository (DERep) or literature).

AND

• Accountable entity-level (measure score-level) reliability and validity testing, when appropriate, and specifications do not need changes based on the results. Measure developers are encouraged to report accountable entity-level reliability results by decile (rather than just the median) to detect differences in reliability across the target population size distribution.
• Completion of face validity testing as the sole type of validity testing does not meet the criteria for completion of testing for a fully developed measure. However, face validity is acceptable for new measures (i.e., those not currently in use in CMS programs and undergoing substantive changes) that are not electronic Clinical Quality Measure (eCQM) . Instead of Likert-scale type assessments of face validity, measure developers are encouraged to develop a logic model consisting of inputs, activities, outputs, and outcomes to describe the associations between the health care structures and processes and the desired health outcome(s). The logic model should indicate the structure(s), process(es), and/or outcome(s) included in the measure. A detailed logic model will help the measure developer identify appropriate constructs for future empiric validity testing.

AND

For measures based on survey data or patient-reported assessment tools, including patient-reported outcome-based performance measures (PRO-PMs), the measure developer has tested reliability and validity of the survey or tool and the survey or tool does not need changes based on the results. For measures based on assessment tools, the measure developer must have completed reliability and validity testing for each critical data element and complete testing of the assessment tool itself with no changes to the tool needed based on the results.