Desirable Attributes of a Quality Measure

The desirable attributes of a quality measure can be grouped into three broad conceptual areas within which narrower categories provide more detail: (1) importance of a measure, (2) scientific soundness of a measure, and (3) feasibility of a measure. Information to guide the user's judgments on many of the important characteristics of a measure described below can be found in NQMC's Template of Measure Attributes.

Importance of the Measure

Relevance to stakeholders - the topic area of the measure is of significant interest, and financially and strategically important to stakeholders (e.g., patients, clinicians, purchasers, public health officers, policy makers).
Health importance - the aspect of health that the measure addresses is important as defined by high prevalence or incidence, and/or a significant effect on the burden of illness (i.e., effect on the mortality and morbidity of a population).
Applicability to measuring the equitable distribution of health care (for health care delivery measures) or of health (for population health measures) - the measure can be stratified or analyzed by subgroup to examine whether disparities in care or of health exist among a diverse population of patients.
Potential for improvement - there is evidence indicating a need for the measure because there is overall poor quality or variations in quality among organizations (for health care delivery measures) or overall poor quality of health or variations in quality of health among populations (for population health measures).
Susceptibility to being influenced by the health care system - for health care delivery measures, the results of the measure relate to actions or interventions that are under the control of those providers whose performance is being measured, so that it is possible for them to improve that performance. For public health measures, the results should be susceptible to influence by the public health system.

Scientific Soundness: Clinical Logic

Explicitness of evidence - the evidence supporting the measure is explicitly stated.
Strength of evidence - the topic area of the measure is strongly supported by the evidence, i.e., indicated to be of great importance for improving quality of care (for health care delivery measures) or improving health (for population health measures).

Scientific Soundness: Measure Properties

Reliability - the results of the measure are reproducible for a fixed set of conditions irrespective of who makes the measurement or when it is made; reliability testing is documented.
Validity - the measure truly measures what it purports to measure; validity testing is documented. See tutorial on measure validity.
Allowance for patient/consumer factors as required - the measure allows for stratification or case-mix adjustment if appropriate.
Comprehensible - the results of the measure are understandable for the user who will be acting on the data.

Feasibility

Explicit specification of numerator and denominator - a measure should usually have explicit and detailed specifications for the numerator and denominator; statements of the requirements for data collection are understandable and implementable. Some measures that do not have explicit and detailed specifications for the numerator and denominator (e.g., measures that have counts or means) can be feasible for quality improvement purposes when used with a specified baseline, benchmark, and/or target.
Data availability - the data source needed to implement the measure is available and accessible within the timeframe for measurement. The costs of abstracting and collecting data are justified by the potential for improvement in care or health.