Glossary

The R2 statistic values describe how well the outcome can be predicted based on the values of the risk factors or predictors. It is frequently used to assess the predictive power of specific types of risk-adjusted models.

A ratio is a score derived by dividing a count of one type of data by a count of another type of data (e.g., number of patients with central lines who develop infection divided by the number of central line days). The key to the definition of a ratio is that the numerator is not in the denominator.

The ROC curve is a graph providing the c-statistic value. The ROC curve graphs the predictive accuracy of a logistic regression model.

Related measures are measures addressing either the same topic or the same population. This term is used when considering harmonization. See also Competing Measures.

Reliability reflects the measure is well defined and precisely specified so measured entities can implement consistently within and across organizations and that it distinguishes differences in performance.

Reliability testing evaluates whether the measure data elements are extracted over time, producing the same results a high proportion of the time when assessed in the same population in the same time period and/or that the measure score is precise. Often referred to as inter-rater or inter-observer reliability, reliability also applies to abstractors and coders. It can also refer to the amount of error associated with the computed measure scores (e.g., signal vs. noise).

Resource use measures, also called cost and resource use measures, refer to broadly applicable and comparable measures of health services counts (in terms of units or dollars) applied to a population or event (broadly defined to include diagnoses, procedures, or encounters). A resource use measure counts the frequency of defined health system resources. Some measures may monetize the health service by applying a dollar amount such as allowable charges, paid amounts, or standardized prices to each unit of resource use.

A respecified measure is an existing measure changed to fit the current purpose or use. This may mean changing a measure to meet the needs of a different care setting, data source, or population; or, it may mean changes to the numerator, denominator, or adding specifications to fit the current use.

Risk adjustment is a mathematical model applied to a quality measure correcting for differing characteristics within a population, such as patient health status. Its purpose is a fairer and more accurate comparison of outcomes of care across health care organizations or clinicians. Measure developers usually apply risk adjustment models to outcome and cost/resource use measures.