Computerized clinical decision support for the early recognition and management of acute kidney injury: a qualitative evaluation of end-user experience

Kanagasundaram, Nigel, Bevan, Mark, Sims, Andrew, Heed, Andrew, Price, David and Sheerin, Neil (2016) Computerized clinical decision support for the early recognition and management of acute kidney injury: a qualitative evaluation of end-user experience. Clinical Kidney Journal, 9 (1). pp. 57-62. ISSN 2048-8505

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Abstract

Background - Although the efficacy of computerized clinical decision support (CCDS) for acute kidney injury (AKI) remains unclear, the wider literature includes examples of limited acceptability and equivocal benefit. Our single-centre study aimed to identify factors promoting or inhibiting use of in-patient AKI CCDS.

Methods - Targeting medical users, CCDS triggered with a serum creatinine rise of ≥25 μmol/L/day and linked to guidance and test ordering. User experience was evaluated through retrospective interviews, conducted and analysed according to Normalization Process Theory. Initial pilot ward experience allowed tool refinement. Assessments continued following CCDS activation across all adult, non-critical care wards.

Results - Thematic saturation was achieved with 24 interviews. The alert was accepted as a potentially useful prompt to early clinical re-assessment by many trainees. Senior staff were more sceptical, tending to view it as a hindrance. ‘Pop-ups’ and mandated engagement before alert dismissal were universally unpopular due to workflow disruption. Users were driven to close out of the alert as soon as possible to review historical creatinines and to continue with the intended workflow.

Conclusions - Our study revealed themes similar to those previously described in non-AKI settings. Systems intruding on workflow, particularly involving complex interactions, may be unsustainable even if there has been a positive impact on care. The optimal balance between intrusion and clinical benefit of AKI CCDS requires further evaluation.

Item Type: Article
Uncontrolled Keywords: acute kidney injury, clinical decision support systems
Subjects: B800 Medical Technology
B900 Others in Subjects allied to Medicine
Department: Faculties > Health and Life Sciences > School of Health, Community and Education Studies > Public Health and Wellbeing
Depositing User: Becky Skoyles
Date Deposited: 24 Jan 2017 11:33
Last Modified: 09 May 2017 00:23
URI: http://nrl.northumbria.ac.uk/id/eprint/29160

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