University of Surrey

Test tubes in the lab Research in the ATI Dance Research

Towards an ontology for data quality in integrated chronic disease management: A realist review of the literature.

Liaw, ST, Rahimi, A, Ray, P, Taggart, J, Dennis, S, de Lusignan, S, Jalaludin, B, Yeo, AE and Talaei-Khoei, A (2012) Towards an ontology for data quality in integrated chronic disease management: A realist review of the literature. Int J Med Inform.

[img] Text
Teng_Ali_Ontologies_Review_20121104_draft.pdf
Restricted to Repository staff only
Available under License : See the attached licence file.

Download (1MB)
[img]
Preview
Text (licence)
SRI_deposit_agreement.pdf

Download (33kB)

Abstract

PURPOSE: 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. CONCLUSION: 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.

Item Type: Article
Subjects : Biosciences and medicine
Authors :
AuthorsEmailORCID
Liaw, STUNSPECIFIEDUNSPECIFIED
Rahimi, AUNSPECIFIEDUNSPECIFIED
Ray, PUNSPECIFIEDUNSPECIFIED
Taggart, JUNSPECIFIEDUNSPECIFIED
Dennis, SUNSPECIFIEDUNSPECIFIED
de Lusignan, SUNSPECIFIEDUNSPECIFIED
Jalaludin, BUNSPECIFIEDUNSPECIFIED
Yeo, AEUNSPECIFIEDUNSPECIFIED
Talaei-Khoei, AUNSPECIFIEDUNSPECIFIED
Date : 1 November 2012
Identification Number : 10.1016/j.ijmedinf.2012.10.001
Depositing User : Symplectic Elements
Date Deposited : 27 May 2016 13:57
Last Modified : 27 May 2016 13:57
URI: http://epubs.surrey.ac.uk/id/eprint/738088

Actions (login required)

View Item View Item

Downloads

Downloads per month over past year


Information about this web site

© The University of Surrey, Guildford, Surrey, GU2 7XH, United Kingdom.
+44 (0)1483 300800