Table 1

Rating matrix domains Desirable Attributes of a Quality Measure—Definitions: The research team has selected the Quality Measures Attributes developed by the Agency for Healthcare Research and Quality (AHRQ) to guide the rating matrix of the Transitions of Care Outcomes/Measures. Table 1 provides a description of each of the desirable attributes of a Quality Measure. For further information of AHRQ's Desirable Attributes of a Quality Measure visit: http://www.qualitymeasures.ahrq.gov.

AHRQ Desirable Attributes of a Quality Measure—Definitions
Quality measure domainCriteria description
Importance of the measureRelevance to stakeholders—the topic area of the measure is of significant interest, and financially and strategically important to stakeholders (eg, 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 (ie, effect on the mortality and morbidity of a population)
Applicability to measuring the equitable distribution of healthcare (for healthcare delivery measures) or of health (for population health measures)—the measure can be stratified or analysed 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 organisations (for healthcare 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 healthcare system—for healthcare 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 logicExplicitness 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, that is,  indicated to be of great importance for improving quality of care (for healthcare delivery measures) or improving health (for population health measures)
Scientific soundness: measure propertiesReliability—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
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
FeasibilityExplicit specification of numerator and denominator—a measure should have explicit and detailed specifications for the numerator and denominator; statements of the requirements for data collection are understandable and implementable
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
  • To ensure measures developed through the panel are useful and relevant over time, you as a panellist are encouraged to consider the extent to which identified measures can be linked to quality of care processes currently, as well as your view as future areas that necessitate attention related to improving transitions of care for medically complex patients across the continuum.

  • In addition to the four AHRQ attributes of a quality measure, two additional criteria for evaluation will be used:

  • ▸ Measuring this is useful in driving transitions of care quality improvement.

  • ▸ Measuring this is useful for accountability purposes such as public reporting.

  • Instructions—You will be asked to rate each of the transitions of care outcomes/measures and/or associated contextual variable identified from the literature review using the following rating matrix (domains of quality measures) on a 9 point Likert Scale ranging from 1 strongly disagree to 9 strongly agree. For example, choosing strongly agree on the “Importance of Measure” reflects your agreement about this particular measure in relation to the criteria description in the AHRQ Desirable Attributes of a Quality Measure provided in Table 1.