Glossary

Data capture, or electronic data capture, is the process of extracting information from a paper or electronic document and converting it into data readable by a computer. Hyland. (n.d.). What is data capture? Retrieved March 20, 2024, from https://www.hyland.com/en/resources/terminology/data-capture/what-is-data-capture

A data element in quality measurement or improvement refers to a specific piece of information that is collected and stored in a healthcare system. Each data element represents a single unit of data and can include various types of data such as patient demographics, clinical measurements, lab results, and treatment details.

Data element validity is the extent to which the information represented by the data element or code used in the measure reflects the actual concept or event intended. For example, use of a medication code as a proxy for a diagnosis code and data element response categories that include all values necessary to provide an accurate response.

See also measure validity.

A data model is an abstract model organizing elements of data and standardizing how they relate to one another. For instance, a data model linking guideline information with clinical data for the patient. Taylor, D. (2023). Data modelling: Conceptual, logical, physical model types. Retrieved March 20, 2024, from https://www.guru99.com/data-modelling-conceptual-logical.html

The De Novo Measure Scan (DNMS) is an advanced feature of the Environmental Scan Support Tool (ESST) on the controlled access CMS Measures Inventory Tool (CMIT) site. You must have a CMIT login to access. The DNMS helps measure developers conduct early and frequent environmental scans while developing new measures. The DNMS uses a Clinical Quality Measure ontology to describe a measure and represent quality measure concepts. Components of the ontology include target population, health status or utilization, change concept, expected output of the change concept, and care setting. The DNMS uses structured search terms to represent the measure concepts to build a new measure and uses artificial intelligence to identify and prioritize the most relevant PubMed, PubMed Central, and CINAHL related literature.

Decision Model and Notation (DNM) is a standard published by the Object Management Group. It is a standard approach for describing and modeling repeatable decisions within organizations to ensure decision models are interchangeable across organizations. Oliveira, W. (2018, August 21) What is decision model and notation (DMN)? Retrieved March 20, 2024, from https://www.heflo.com/blog/process-modeling/decision-model-and-notation-dmn/

The denominator is the lower part of a fraction used to calculate a rate, proportion, or ratio. It can be the same as the initial population or a subset of the initial population to further constrain the population for the purpose of the measure. Continuous variable measures do not have a denominator, but instead define a measure population.

A denominator exception is any condition that should remove a patient, procedure, or unit of measurement from the denominator of the performance rate only if the numerator criteria are not met. A denominator exception allows for adjustment of the calculated score for those measured entities with higher risk populations. A denominator exception also provides for the exercise of clinical judgment and the measure developer should specifically define where to capture the information in a structured manner that fits the clinical workflow. The measured entity removes denominator exception cases from the denominator. However, the measured entity may still report the number of patients with valid exceptions. Allowable reasons fall into three general categories - medical reasons, patient reasons, or system reasons. Only proportion measures use a denominator exception.

A denominator exclusion is a case the measured entity should remove from the measure population and denominator before determining if numerator criteria are met. Proportion and ratio measures use denominator exclusions to help narrow the denominator. For example, a measure developer would list patients with bilateral lower extremity amputations as a denominator exclusion for a measure requiring foot exams. Continuous variable measures may use denominator exclusions but may use the term measure population exclusion instead of denominator exclusion.

The Health Level Seven International (HL7®) Data Exchange for Quality Measures (DEQM) Implementation Guide (IG) defines conformance profiles and implementation guidance to support the interoperable exchange of quality measurement and quality improvement data. The IG enables use cases such as transferring quality reporting information between healthcare providers and payers using Fast Healthcare Interoperability Resources (FHIR®)-based resources.

The DEQM IG supports multiple reporting scenarios, including:

• Individual reporting
• Subject list reporting
• Summary reporting
• Gaps in care reporting

The DEQM Individual MeasureReport profile supports individual-level reporting and is intended to replace the Quality Reporting Document Architecture (QRDA) Category I format. The DEQM Summary MeasureReport profile supports aggregate-level reporting and is intended to replace the QRDA Category III format.

The HL7 Clinical Quality Information Work Group (CQI) manages development and updates to the DEQM IG through the HL7 standards balloting process. The publication cycle is aligned with the Quality Measure IG and the Quality Improvement Core (QI-Core) IG to ensure consistency across FHIR-based quality measurement specifications.

Derivative products, with respect to clinical practice guidelines, are products with content derived from the content of the practice guideline, e.g., clinical decision support, patient/family guides, pocket cards, phone apps for clinicians, continuing education programs.

CMS defines digital quality measures (dQMs) as quality measures that use standardized, digital data from one or more sources of health information that are captured and exchanged via interoperable systems; apply quality measure specifications that are standards-based and use code packages; and are computable in an integrated environment.

A direct reference code (DRC) is a specific code referenced directly in the electronic clinical quality measure logic to describe a data element or one of its attributes. DRC metadata include the description of the code, the code system including the code, and the version of that code system.

The Quality Measure Implementation Guide includes examples of digital quality measures (dQMs) using Fast Healthcare Interoperability Resources® (FHIR®).