Glossary

The importance criterion assesses the extent to which the specific measure focus is evidence-based and important to making significant gains in health care quality (e.g., safety, timeliness, effectiveness, efficiency, equity, patient-centeredness) and improving health outcomes for a specific high-impact aspect of health care where there is variation in or overall poor performance. 

Industry standard modeling techniques use a standard visual approach to facilitate communication related to business models and software design. For example, Unified Modeling Language (UML) uses integrated diagrams to specify and document the structure and dynamic behavior of information system and software artifacts.

Informatics activities include tasks related to knowledge engineering and technical development of clinical practice guidelines artifacts (L2 to L4). These may include, but not limited to developing use case diagrams, flow diagrams, and decision trees; identifying relevant data elements, Fast Healthcare Interoperability Resources® profiles, terminologies, value sets, libraries, rules, and logic representations; writing software code (e.g., for clinical decision support); and developing comprehensive test cases and testing resources.

With an integrated process, steps related to guideline development, informatics activities, implementation, evaluation, and communications are conducted in parallel, insofar as possible, rather than in sequence.

An intensional value set is a list of codes based on a logical statement that often has an algorithmic basis for selection of concepts.

An interested party is an individual, group, or organization affected by the outcome of a project and, thus, has an interest in the project's success.

An intermediate outcome measure is a measure assessing the change produced by a health care intervention leading to a long-term outcome.

An inverse measure is a measure in which 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 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.