Developing a Standards-Based Information Model for Representing Computable Diagnostic Criteria: A Feasibility Study of the NQF Quality Data Model

Guoqian Jiang, Harold R. Solbrig, Jyotishman Pathak, Christopher G. Chute

Research output: Chapter in Book/Report/Conference proceedingConference contribution

2 Scopus citations

Abstract

The lack of a standards-based information model has been recognized as a major barrier for representing computable diagnostic criteria. In this paper we describe our efforts in examining the feasibility of the Quality Data Model (QDM)-developed by the National Quality Forum (NQF)-for representing computable diagnostic criteria. We collected the diagnostic criteria for a number of diseases and disorders (n=12) from textbooks and profiled the data elements of the criteria using the QDM data elements. We identified a number of common patterns informed by the QDM. In conclusion, the common patterns informed by the QDM are useful and feasible in building a standards-based information model for computable diagnostic criteria.

Original languageEnglish (US)
Title of host publicationMEDINFO 2015
Subtitle of host publicationeHealth-Enabled Health - Proceedings of the 15th World Congress on Health and Biomedical Informatics
EditorsAndrew Georgiou, Indra Neil Sarkar, Paulo Mazzoncini de Azevedo Marques
PublisherIOS Press
Pages1097
Number of pages1
ISBN (Electronic)9781614995630
DOIs
StatePublished - 2015
Event15th World Congress on Health and Biomedical Informatics, MEDINFO 2015 - Sao Paulo, Brazil
Duration: Aug 19 2015Aug 23 2015

Publication series

NameStudies in Health Technology and Informatics
Volume216
ISSN (Print)0926-9630
ISSN (Electronic)1879-8365

Other

Other15th World Congress on Health and Biomedical Informatics, MEDINFO 2015
Country/TerritoryBrazil
CitySao Paulo
Period8/19/158/23/15

Keywords

  • Diagnostic Criteria
  • ICD-11 Content Model
  • ISO 11179 Model
  • Quality Data Model (QDM)

ASJC Scopus subject areas

  • Biomedical Engineering
  • Health Informatics
  • Health Information Management

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