Evidence map›Paper›PMID 37823061›Full record

ArticleJournal of cognitive engineering and decision making2023

Decision-Making During High-Risk Events: A Systematic Literature Review.

Carrie Reale, Megan E Salwei, Laura G Militello, Matthew B Weinger, Amanda Burden, Christen Sushereba, Laurence C Torsher, Michael H Andreae, David M Gaba, William R McIvor and 3 more

Abstract read
In one paragraph

Article in Journal of cognitive engineering and decision making, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 20 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
20citing papers in PubMed, 1 pooled it
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

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.

2 · The registry

The trial behind it

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.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

20 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Pooled it
  2. Trial
  3. Article
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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

13 authors.

Carrie RealeCenter for Research and Innovation in Systems Safety, Department of Anesthesiology and the Center for Health Services Research, Institute for Medicine and Public Health, Vanderbilt University Medical Center, Nashville, TN, USA.ORCID 0000-0002-9011-2692
Megan E SalweiCenter for Research and Innovation in Systems Safety, Department of Anesthesiology and the Center for Health Services Research, Institute for Medicine and Public Health, Vanderbilt University Medical Center, Nashville, TN, USA, Department of Biomedical Informatics, Vanderbilt University Medical Center, Nashville, TN, USA.
Laura G MilitelloApplied Decision Science, LLC, Dayton, OH, USA.ORCID 0000-0001-8445-5640
Matthew B WeingerCenter for Research and Innovation in Systems Safety, Department of Anesthesiology and the Center for Health Services Research, Institute for Medicine and Public Health, Vanderbilt University Medical Center, Nashville, TN, USA, Department of Biomedical Informatics, Vanderbilt University Medical Center, Nashville, TN, USA.
Amanda BurdenDepartment of Anesthesiology, Cooper Medical School of Rowan University, Camden, NJ, USA.
Christen SusherebaApplied Decision Science, LLC, Dayton, OH, USA.ORCID 0000-0001-7523-9671
Laurence C TorsherDepartment of Anesthesiology and Perioperative Medicine, Mayo Clinic, Rochester, MN, USA.
Michael H AndreaeDepartment of Anesthesiology, School of Medicine, University of Utah, Salt Lake City, UT, USA.ORCID 0000-0002-9052-0936
David M GabaPatient Simulation Center, VA Palo Alto Healthcare System, Palo Alto, CA, USA, Department of Anesthesiology, Perioperative & Pain Medicine, Stanford School of Medicine, Stanford University, Stanford, CA, USA.
William R McIvorDepartment of Anesthesiology, School of Medicine, University of Pittsburgh, Pittsburgh, PA, USA.
Arna BanerjeeCenter for Research and Innovation in Systems Safety, Department of Anesthesiology and the Center for Health Services Research, Institute for Medicine and Public Health, Vanderbilt University Medical Center, Nashville, TN, USA.
Jason SlagleCenter for Research and Innovation in Systems Safety, Department of Anesthesiology and the Center for Health Services Research, Institute for Medicine and Public Health, Vanderbilt University Medical Center, Nashville, TN, USA.
Shilo AndersCenter for Research and Innovation in Systems Safety, Department of Anesthesiology and the Center for Health Services Research, Institute for Medicine and Public Health, Vanderbilt University Medical Center, Nashville, TN, USA, Department of Biomedical Informatics, Vanderbilt University Medical Center, Nashville, TN, USA.

Funding

Vanderbilt Biomedical Informatics Training ProgramT15LM007450 · NLM · VANDERBILT UNIVERSITY · PI Jessica S. Ancker, Bradley A. Malin · 2002 to 2026
$19.7M
Learning Health System Scholar Program at VanderbiltK12HS026395 · AHRQ · VANDERBILT UNIVERSITY MEDICAL CENTER · PI ROTHMAN, RUSSELL L., ROUMIE, CHRISTIANNE L. · 2018 to 2022
$2.7M
IMPACTS: Improving Medical Performance during Acute Crises Through SimulationR18HS026158 · AHRQ · VANDERBILT UNIVERSITY MEDICAL CENTER · PI WEINGER, MATTHEW BRET · 2018 to 2022
$2.0M
COMputerized PAtient-centered Collaborative Technology (COMPACT) to Support Personalized Decision Making in Breast CancerK01HS029042 · AHRQ · VANDERBILT UNIVERSITY MEDICAL CENTER · PI SALWEI, MEGAN ELIZABETH · 2022 to 2025
$494k
AHRQ HHS K01 HS029042AHRQ HHS K12 HS026395AHRQ HHS R18 HS026158NLM NIH HHS T15 LM007450
6 · The paper itself

Abstract

Effective decision-making in crisis events is challenging due to time pressure, uncertainty, and dynamic decisional environments. We conducted a systematic literature review in PubMed and PsycINFO, identifying 32 empiric research papers that examine how trained professionals make naturalistic decisions under pressure. We used structured qualitative analysis methods to extract key themes. The studies explored different aspects of decision-making across multiple domains. The majority (19) focused on healthcare; military, fire and rescue, oil installation, and aviation domains were also represented. We found appreciable variability in research focus, methodology, and decision-making descriptions. We identified five main themes: (1) decision-making strategy, (2) time pressure, (3) stress, (4) uncertainty, and (5) errors. Recognition-primed decision-making (RPD) strategies were reported in all studies that analyzed this aspect. Analytical strategies were also prominent, appearing more frequently in contexts with less time pressure and explicit training to generate multiple explanations. Practitioner experience, time pressure, stress, and uncertainty were major influencing factors. Professionals must adapt to the time available, types of uncertainty, and individual skills when making decisions in high-risk situations. Improved understanding of these decisional factors can inform evidence-based enhancements to training, technology, and process design.

Indexed as

decision-makingdecision-making strategyerrorshealthcarehigh-risk eventsnaturalistic decision-makingrecognition-primed decision-makingsimulationstresstime pressureuncertainty

Identifiers

PMID37823061
PMCPMC10564111

What OpenQuestion holds

Textmetadata
LicenceTDM
Read underepoch 390

Registered trials

None linked

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.