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Measure Conceptualization

Analyze Data & Conduct Gap Analysis

Review and Analyze Empirical Data, as Appropriate

If empirical data are available, measure developers should analyze the data statistically to support the importance of the measure, identify gaps or variations in care, and provide incidence/prevalence information and other data, e.g., return on investment (ROI), necessary for development of the business case. Empirical data analysis may also provide quantitative evidence for inclusion or denominator exclusion and numerator exclusion of a set of populations or geographic regions or other considerations for development of the measure. 

Measure developers can also analyze empirical data to test the feasibility of data elements required for a measure, such as data availability (including standardization) and accuracy of data information. They may use empirical data to help identify feasibility concerns early in development of the measure. Measure developers may need to replace or revise data elements, consider an alternative measure type, assess implementation burden versus value of the measure, or recommend halting further development of the measure concept.

If developing a risk-adjusted measure, measure developers should assess feasibility of the risk variables early on. See the Risk Adjustment in Quality Measurement supplemental material. 

Evaluate Information Collected During the Environmental Scan and Empirical Data Analysis

If the environmental scan discovers related measures, measure developers should evaluate the measures to assess whether they meet the needs of the project. If the measure developer finds a related measure with a measure focus appropriate to the needs of the project, but the measure specification is for a different population, setting, or data source, the measure developer may be able to respecify the measure for the new use and test it for reliability and validity specific to the new population. 

Conduct a Measurement Gap Analysis to Identify Areas for New Measure Development

The purpose of a gap analysis is to identify measure types or concepts that may be missing for the measure topic or focus. The measure developer uses information collected from the environmental scan, measure gap analysis, and other information gathering activities to identify existing competing or related measures before deciding to develop new measures. If no related or competing measures can be respecified or adopted, then it is appropriate to develop a new measure. Measure developers should establish a framework to organize any existing measures, for example to break down existing measures by measure component and data elements to help identify overlaps and gaps. 

Last Updated: Nov 2022