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Published on: September 26, 2018
The implementation challenge of computerised clinical decision support systems for the detection of disease in
Christina Derksen1, Fiona M Walter2, Adriana B Akbar3
1Wolfson Institute of Population Health, Faculty of Medicine and Dentistry, Queen Mary University of London, London, UK. christina.derksen@qmul.ac.uk.
Background:
Early detection of diseases in primary care is crucial for timely treatment and better outcomes. Complex care demands and limited resources can make early detection challenging. Clinical decision support systems (CDSS) aim to improve the diagnostic process. However, barriers to implementation have so far prevented their effective use. This systematic review aimed to identify barriers for the implementation of CDSS for disease detection in primary care and use this to develop recommendations for implementation.
Methods:
We searched MEDLINE, EMBASE, Scopus, Web of Science and Cochrane databases. Included studies reported barriers to the implementation of CDSS for the detection of undiagnosed, prevalent diseases in primary care. Two independent researchers undertook screening and data extraction. The QuADS tool was used for quality assessment. Data on barriers and facilitators were synthesised using an inductive-deductive approach based on the Theoretical Domains Framework. This was used to identify solutions via the Behaviour Change Wheel.
Results:
10498 titles and abstracts were screened, and 768 full texts were assessed. We included 99 studies describing 85 tools, mostly in high-income countries. Most studies (66, 66.7%) applied qualitative methods and described CDSS implemented in pilot studies (64, 64.7%). Included studies had very limited stakeholder involvement or theoretical underpinning. We identified 2563 unique barriers and facilitators to implementation. Barriers were spread across the Theoretical Domains Framework including technical and workflow implementation issues at practice level, wider healthcare system issues, problems with the usability of systems, PCPs' and patients' attitudes and beliefs, a lack of skills and knowledge, and social barriers. Implementation recommendations for development teams involve selecting appropriate diagnostic challenges for CDSS, ensuring usability, engaging stakeholders and testing CDSS prior to implementation. Primary care teams need to clarify responsibilities, provide training and support patients. Underlying barriers across healthcare systems will need to be addressed at policy level.
Conclusions:
The range and scale of the barriers and complexity of recommendations highlight implementation challenges for CDSS in primary care. Although recommendations can be used to improve implementation, our findings emphasise the need to carefully reflect on the feasibility of CDSS in primary care at the point of design and development. The systematic review was preregistered using PROSPERO (CRD42024517054): https://www.crd.york.ac.uk/prospero/display_record.php?RecordID=517054.
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