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

Nigel Kanagasundaram, Mark Bevan, Andrew Sims, Andrew Heed, David Price, Neil Sheerin

Research output: Contribution to journalArticlepeer-review

19 Citations (Scopus)
26 Downloads (Pure)

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.
Original languageEnglish
Pages (from-to)57-62
JournalClinical Kidney Journal
Volume9
Issue number1
Early online date18 Dec 2015
DOIs
Publication statusPublished - Feb 2016

Keywords

  • acute kidney injury
  • clinical decision support systems

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