ArticleJournal of patient safety2025
Understanding Clinical Decision Support Failures in Pediatric Intensive Care Units via Applied Systems Safety Engineering and Human Factors Problem Analysis: Insights From the DISCOVER Learning Lab.
Article in Journal of patient safety, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
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Who cites it
1 citing paper in PubMed.
- Comment on "Multidisciplinary neonatal acute kidney injury provider perceptions and practice patterns".Pediatric nephrology (Berlin, Germany) · 2026Article
Corrections and comments
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Authors and funding
12 authors.
Funding
Abstract
objectivesChildren receiving care in pediatric intensive care units (PICUs) are vulnerable to decompensation and diagnostic error due to the complex and dynamic nature of pediatric critical illness. In the PICU, the few clinical decision support (CDS) tools that have been implemented to support diagnostic accuracy (i.e., the ability to detect the presence of a condition) have not led to an increase in clinician adoption of desired practices nor demonstrated clear clinical benefit.
methodsThe DISCOVER Learning Lab analyzed workflow and failure modes in diagnosing and managing clinical decompensation in the PICU, using systems safety engineering and human factors to examine intersections with established CDS. Methods employed included qualitative interviews, workflow mapping, immersive virtual reality (VR) systems testing via a digital twin environment, and a failure modes effect analysis.
resultsWorkflow mapping and qualitative interviews revealed barriers to communication, workflow inefficiencies, and limited access to up-to-date clinical information during critical events in the PICU. The immersive VR systems testing elucidated how PICU staff members currently interact with CDS tools and how various tools could better integrate into or influence clinical workflows. Critical failure modes were identified with corresponding opportunity areas for intervention.
conclusionsThe application of a systems safety engineering and human factors approach to problem analysis, partnered with novel use of immersive VR and digital twin technology, led to valuable insights into common failure modes and potential opportunity areas to improve diagnostic accuracy and care delivery in a quaternary referral center PICU.
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