title: Towards an ontology for data quality in integrated chronic disease management: a realist review of the literature.
abstract: OBJECTIVE
  Effective use of routine data to support integrated chronic disease management (CDM) and population health is dependent on underlying data quality (DQ) and, for cross system use of data, semantic interoperability. An ontological approach to DQ is a potential solution but research in this area is limited and fragmented.
  
  
  OBJECTIVE
  Identify mechanisms, including ontologies, to manage DQ in integrated CDM and whether improved DQ will better measure health outcomes.
  
  
  METHODS
  A realist review of English language studies (January 2001-March 2011) which addressed data quality, used ontology-based approaches and is relevant to CDM.
  
  
  RESULTS
  We screened 245 papers, excluded 26 duplicates, 135 on abstract review and 31 on full-text review; leaving 61 papers for critical appraisal. Of the 33 papers that examined ontologies in chronic disease management, 13 defined data quality and 15 used ontologies for DQ. Most saw DQ as a multidimensional construct, the most used dimensions being completeness, accuracy, correctness, consistency and timeliness. The majority of studies reported tool design and development (80%), implementation (23%), and descriptive evaluations (15%). Ontological approaches were used to address semantic interoperability, decision support, flexibility of information management and integration/linkage, and complexity of information models.
  
  
  CONCLUSIONS
  DQ lacks a consensus conceptual framework and definition. DQ and ontological research is relatively immature with little rigorous evaluation studies published. Ontology-based applications could support automated processes to address DQ and semantic interoperability in repositories of routinely collected data to deliver integrated CDM. We advocate moving to ontology-based design of information systems to enable more reliable use of routine data to measure health mechanisms and impacts.
authors.affiliation: University of NSW School of Public Health & Community Medicine, Sydney, Australia. siaw@unsw.edu.au
authors.forename: S T
authors.initials: ST
authors.lastname: Liaw
authors.forename: A
authors.initials: A
authors.lastname: Rahimi
authors.forename: P
authors.initials: P
authors.lastname: Ray
authors.forename: J
authors.initials: J
authors.lastname: Taggart
authors.forename: S
authors.initials: S
authors.lastname: Dennis
authors.forename: S
authors.initials: S
authors.lastname: de Lusignan
authors.forename: B
authors.initials: B
authors.lastname: Jalaludin
authors.forename: A E T
authors.initials: AE
authors.lastname: Yeo
authors.forename: A
authors.initials: A
authors.lastname: Talaei-Khoei
mesh_terms: D002908:Chronic Disease; D003625:Data Collection; D019468:Disease Management; D006801:Humans; D019451:Information Management; D008498:Medical Record Linkage; D012107:Research Design