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Ten misconceptions regarding decision-making in critical care.

作者信息

Ramaswamy Tara, Sparling Jamie L, Chang Marvin G, Bittner Edward A

机构信息

Department of Anesthesiology, Perioperative and Pain Medicine, Stanford University School of Medicine, Stanford, CA 94305, United States.

Department of Anesthesia, Critical Care and Pain Medicine, Massachusetts General Hospital, Harvard Medical School, Boston, MA 02114, United States.

出版信息

World J Crit Care Med. 2024 Jun 9;13(2):89644. doi: 10.5492/wjccm.v13.i2.89644.


DOI:10.5492/wjccm.v13.i2.89644
PMID:38855268
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC11155500/
Abstract

Diagnostic errors are prevalent in critical care practice and are associated with patient harm and costs for providers and the healthcare system. Patient complexity, illness severity, and the urgency in initiating proper treatment all contribute to decision-making errors. Clinician-related factors such as fatigue, cognitive overload, and inexperience further interfere with effective decision-making. Cognitive science has provided insight into the clinical decision-making process that can be used to reduce error. This evidence-based review discusses ten common misconceptions regarding critical care decision-making. By understanding how practitioners make clinical decisions and examining how errors occur, strategies may be developed and implemented to decrease errors in Decision-making and improve patient outcomes.

摘要

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本文引用的文献

[1]
Defining a High-Quality and Effective Morbidity and Mortality Conference: A Systematic Review.

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[2]
Preparing Physicians for the Clinical Algorithm Era.

N Engl J Med. 2023-8-10

[3]
Sources of bias in artificial intelligence that perpetuate healthcare disparities-A global review.

PLOS Digit Health. 2022-3-31

[4]
Difficult diagnosis in the ICU: making the right call but beware uncertainty and bias.

Anaesthesia. 2023-4

[5]
Clinical Algorithms, Antidiscrimination Laws, and Medical Device Regulation.

JAMA. 2023-1-24

[6]
Artificial intelligence-aided diagnosis model for acute respiratory distress syndrome combining clinical data and chest radiographs.

Digit Health. 2022-8-15

[7]
Reconsidering the application of systems thinking in healthcare: the RaDonda Vaught case.

Br J Anaesth. 2022-9

[8]
Autopsy study of fatal invasive pulmonary aspergillosis: Often undiagnosed premortem.

Respir Med. 2022-8

[9]
Decision Making: Healthy Heuristics and Betraying Biases.

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[10]
Dual Process Theory and Cognitive Load: How Intensivists Make Diagnoses.

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