ReviewCritical care (London, England)2025
Human judgment error in the intensive care unit: a perspective on bias and noise.
Review in Critical care (London, England), 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.
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.
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Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
4 citing papers in PubMed.
- The ICUPASS Study: Variability, Influencing Factors, and Clinician Stress in ICU Admission Decisions.Cureus · 2026Article
- Cultural transformation beyond checklists for patient safety: a longitudinal evaluation of safety interventions in critical care.BMJ open quality · 2026Article
- Evaluating the o1 reasoning large language model for cognitive bias: a vignette study.Critical care (London, England) · 2025Article
- A large language model improves clinicians' diagnostic performance in complex critical illness cases.Critical care (London, England) · 2025Article
Corrections and comments
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Authors and funding
6 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundIn the Intensive Care Unit (ICU), clinicians frequently make complex, high-stakes judgments, where inaccuracies can profoundly affect patient outcomes. This perspective examines human judgment error in ICU settings, specifically bias (systematic error) and noise (random error). While past research has emphasized bias, we explore the role of noise in clinical decision making and its mitigation. MAIN BODY: System noise refers to unwanted variability in judgments that should ideally be identical. This variability stems from level noise (variability in clinicians' average judgments), stable pattern noise (variability in clinicians' responses to specific patient characteristics), and occasion noise (random, within-clinician variability). Two strategies to reduce noise are the use of algorithms and the averaging of independent judgments.
conclusionRecognizing and addressing noise in clinical decision making is essential to enhancing judgment accuracy in critical care. By implementing effective noise reduction strategies, clinicians can reduce errors and improve patient outcomes, ultimately advancing the quality of care delivered in ICU settings.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.