The Importance criterion allows for a distinction between things that are important to do (or outcomes of importance) versus those processes, structures, or outcomes that rise to the level of importance required for a national performance measure. Importance has two key sub-criteria: evidence and performance gap. Evidence is the extent to which the specific measure focus is evidence-based and can drive significant gains in healthcare quality. Performance gap denotes that there is variation in performance among measured entities or that disparities (e.g., by race or ethnicity) exist even if a "macro-level" analysis appears to show that a measure is topped out. Source: National Quality Forum. (2018). Measure Evaluation Criteria and Guidance for Evaluating Measures for Endorsement document.
The initial population refers to all events to be evaluated by a specific electronic clinical quality measure (eCQM) involving patients who share a common set of specified characteristics within a specific measurement set to which a given measure belongs. All patients counted (for example, as numerator, as denominator) are drawn from the initial population.
An intermediate outcome is a (measured) change in physiologic state that leads to a longer-term health outcome. There should be a body of evidence that the measured intermediate clinical outcome leads to a desired health outcome.
An inverse measure is a measure where a lower performance rate is better. Therefore, a zero performance rate for these measures is a good score. For example,the National Healthcare Safety Network calculates most Healthcare-Associated Infections (HAIs) as a standardized infection ratio (SIR). The SIR compares the actual number of HAIs (the numerator) with the predicted number based on the baseline U.S. experience (e.g., standard population), adjusting for several risk factors that have been found to be most associated with differences in infection rates. The goal is to have the numerator equal to or very close to zero thereby having an SIR equal to or very close to zero.