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Conceptual analysis of a diverse set of healthcare quality indicators

White, P. & Roudsari, A. (2015). Conceptual analysis of a diverse set of healthcare quality indicators. Studies in Health Technolology & Informatics, 208, pp. 347-351. doi: 10.3233/978-1-61499-488-6-347


Ontologies, described as a specification of a representational vocabulary for a shared domain of discourse [1], can facilitate automated quality monitoring by categorising and establishing relationships between concepts. In terms of ontology development, conceptualisation is the informal representation of domain terms in the form of concepts, instances, relations, and properties [2]. Chan et al [3] suggest a need for research into attributes of quality indicators to support electronic health record (EHR) compatibility. Identification of levels of indicator relationships can serve as a step towards repackaging formulas into reusable components.

A 2009 set of over 200 indicators, collated by the English National Health Service Health and Social Care Information Centre (NHS HSCIC) was chosen to attempt to address some of the gaps in research exploring ontologies and healthcare quality indicators [4]. The gaps included: research on healthcare quality indicator purposes, an ontology for healthcare quality indicators that is not dependent on data available in EHRs, an ontology that covers many clinical subject areas, and a healthcare quality indicator ontology that does not require a framework for indicator development.

We set out to identify relationships and layers of inclusion and exclusion criteria for a large, diverse set of quality indicators from the English NHS. The indicators, originating from different sources ranging from the UK Renal Registry to the NHS Quality and Outcomes Framework, are measures related to processes and outcomes. Our analysis served as the conceptualisation stage for an ontology for the indicators.

Publication Type: Article
Additional Information: IOS Press Copyright 2012; Non-commercial use only
Subjects: Q Science > QA Mathematics > QA75 Electronic computers. Computer science
Departments: School of Science & Technology > Computer Science
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