A systematic literature review on unnecessary diagnostic testing: The role of ICT use

Lu Bai; Shijia Gao; Frada Burstein; Donald Kerr; Paul Buntine; Nicholas Law

doi:10.1016/j.ijmedinf.2020.104269

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A systematic literature review on unnecessary diagnostic testing: The role of ICT use

Journal article

Peer reviewed

A systematic literature review on unnecessary diagnostic testing: The role of ICT use

Lu Bai, Shijia Gao, Frada Burstein, Donald Kerr, Paul Buntine and Nicholas Law

International Journal of Medical Informatics, Vol.143, pp.1-9

2020

DOI: https://doi.org/10.1016/j.ijmedinf.2020.104269

PMID: 32927268

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Abstract

Information and communications technology-based (ICT-based) intervention

Diagnostic testing

Systematic review

The negative impact of unnecessary diagnostic tests on healthcare systems and patients has been widely recognized. Medical researchers in various countries have been devoting effort to reduce unnecessary diagnostic tests by using different types of interventions, including information and communications technology-based (ICT-based) intervention, educational intervention, audit and feedback, the introduction of guidelines or protocols, and the reward and punishment of staff. We conducted a review of ICT based interventions and a comparative analysis of their relative effectiveness in reducing unnecessary tests.

Details

Title: A systematic literature review on unnecessary diagnostic testing: The role of ICT use
Authors: Lu Bai (Author) - Monash University
Shijia Gao (Author) - Monash University
Frada Burstein (Author) - Monash University
Donald Kerr (Author) - University of the Sunshine Coast, Queensland, USC Business School - Legacy
Paul Buntine (Author) - Box Hill Hospital
Nicholas Law (Author) - Sibu Hospital
Publication details: International Journal of Medical Informatics, Vol.143, pp.1-9
Publisher: Elsevier Ireland Ltd.
Date published: 2020
DOI: 10.1016/j.ijmedinf.2020.104269
ISSN: 1872-8243
PMID: 32927268
Organisation Unit: University of the Sunshine Coast, Queensland; USC Business School - Legacy
Language: English
Record Identifier: 99479407002621
Output Type: Journal article

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17 Times Cited - Web of Science

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Collaboration types: Domestic collaboration; International collaboration
Web Of Science research areas: Computer Science, Information Systems; Health Care Sciences & Services; Medical Informatics

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Source: SDGs from InCites