Achieving Quality in Clinical Decision Making: Cognitive Strategies and Detection of Bias
Abstract
Clinical decision making is a cornerstone of high‐quality care in emergency medicine. The density of decision making is unusually high in this unique milieu, and a combination of strategies has necessarily evolved to manage the load. In addition to the traditional hypothetico‐deductive method, emergency physicians use several other approaches, principal among which are heuristics. These cognitive short‐cutting strategies are especially adaptive under the time and resource limitations that prevail in many emergency departments (EDs), but occasionally they fail. When they do, we refer to them as cognitive errors. They are costly but highly preventable. It is important that emergency physicians be aware of the nature and extent of these heuristics and biases, or cognitive dispositions to respond (CDRs). Thirty are catalogued in this article, together with descriptions of their properties as well as the impact they have on clinical decision making in the ED. Strategies are delineated in each case, to minimize their occurrence. Detection and recognition of these cognitive phenomena are a first step in achieving cognitive de‐biasing to improve clinical decision making in the ED.
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Providers make decisions at different points in medical emergencies.
“As in this study and prior work [17], providers make decisions at different points in medical emergencies.”
From To Recommend or Not to Recommend: Designing and Evaluating AI-Enabled Decision Support for Time-Critical Medical Events (2025) · cites this paper as [17]
Cites
Tversky, A., & Kahneman, D. (1974) · Science · doi:10.1126/science.185.4157.1124 · Cited by 28,810 · see citing works
Availability: A heuristic for judging frequency and probability
Tversky, A., & Kahneman, D. (1973) · Cognitive Psychology · doi:10.1016/0010-0285(73)90033-9 · Cited by 9,984 · see citing works
REMEMBERING: A STUDY IN EXPERIMENTAL AND SOCIAL PSYCHOLOGY
Bartlett, F. C., & Burt, C. (1933) · British Journal of Educational Psychology · doi:10.1111/j.2044-8279.1933.tb02913.x · Cited by 7,475 · see citing works
On the psychology of prediction.
Kahneman, D., & Tversky, A. (1973) · Psychological Review · doi:10.1037/h0034747 · Cited by 6,202 · see citing works
Reason, J. (1990) · doi:10.1017/cbo9781139062367 · Cited by 5,108 · see citing works
Support theory: a nonextensional representation of subjective probability
Tversky, A., & Koehler, D. J. (1994) · Psychological Review · doi:10.1037/0033-295x.101.4.547 · Cited by 1,167 · see citing works
Outcome Bias in Decision Evaluation
Baron, J., & Hershey, J. C. (1988) · Journal of Personality and Social Psychology · doi:10.1037/0022-3514.54.4.569 · Cited by 873 · see citing works
Reluctance to vaccinate: Omission bias and ambiguity
Ritov, I., & Baron, J. (1990) · Journal of Behavioral Decision Making · doi:10.1002/bdm.3960030404 · Cited by 854 · see citing works
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Cited by
Sorted by citations
The Importance of Cognitive Errors in Diagnosis and Strategies to Minimize Them
Croskerry, P. (2003) · Academic Medicine · doi:10.1097/00001888-200308000-00003 · Cited by 1,675 · see citing works
Self-citationDiagnostic error in internal medicine
Graber, M. L., Franklin, N., & Gordon, R. (2005) · Archives of Internal Medicine · doi:10.1001/archinte.165.13.1493 · Cited by 1,549 · see citing works
A Universal Model of Diagnostic Reasoning
Croskerry, P. (2009) · Academic Medicine · doi:10.1097/acm.0b013e3181ace703 · Cited by 1,016 · see citing works
Self-citationSocial Data: Biases, Methodological Pitfalls, and Ethical Boundaries
Olteanu, A., Castillo, C., Diaz, F., & Kıcıman, E. (2019) · Frontiers in Big Data · doi:10.3389/fdata.2019.00013 · Cited by 763 · see citing works
“…been studied across many disciplines such as social science, cognitive psychology or law, and encompasses phenomena such as confirmation bias and other cognitive biases (Croskerry, 2002), as well as systemic, discriminatory outcomes (Friedman and Nissenbaum, 1996) or harms (Barocas et al., 2017).”
BackgroundCognitive forcing strategies in clinical decisionmaking
Croskerry, P. (2003) · Annals of Emergency Medicine · doi:10.1067/mem.2003.22 · Cited by 440 · see citing works
Self-citationCognitive and System Factors Contributing to Diagnostic Errors in Radiology
Lee, C. S., Nagy, P. G., Weaver, S. J., & Newman-Toker, D. E. (2013) · American Journal of Roentgenology · doi:10.2214/ajr.12.10375 · Cited by 415 · see citing works
Implicit bias in healthcare: clinical practice, research and decision making
Gopal, D. P., Chetty, U., O'Donnell, P., Gajria, C., & Blackadder-Weinstein, J. (2021) · Future Healthcare Journal · doi:10.7861/fhj.2020-0233 · Cited by 298 · see citing works
Bias in Radiology: The How and Why of Misses and Misinterpretations
Busby, L. P., Courtier, J. L., & Glastonbury, C. M. (2018) · RadioGraphics · doi:10.1148/rg.2018170107 · Cited by 277 · see citing works
The Role of Large Language Models in Medical Education: Applications and Implications
Safranek, C. W., Sidamon-Eristoff, A. E., Gilson, A., & Chartash, D. (2023) · JMIR Medical Education · doi:10.2196/50945 · Cited by 233 · see citing works
Dual-process cognitive interventions to enhance diagnostic reasoning: a systematic review
Lambe, K. A., O'Reilly, G., Kelly, B. D., & Curristan, S. (2016) · BMJ Quality & Safety · doi:10.1136/bmjqs-2015-004417 · Cited by 215 · see citing works
Understanding diagnostic errors in medicine: a lesson from aviation
Singh, H. (2006) · Quality and Safety in Health Care · doi:10.1136/qshc.2005.016444 · Cited by 156 · see citing works
How Clinical Decisions Are Made
Bate, L., Hutchinson, A., Underhill, J., & Maskrey, N. (2012) · British Journal of Clinical Pharmacology · doi:10.1111/j.1365-2125.2012.04366.x · Cited by 131 · see citing works
Re-visioning risk assessment for human service decision making
Schwalbe, C. (2004) · Children and Youth Services Review · doi:10.1016/j.childyouth.2004.02.011 · Cited by 94 · see citing works
Diagnostic error in medical education: where wrongs can make rights
Eva, K. W. (2009) · Advances in Health Sciences Education · doi:10.1007/s10459-009-9188-9 · Cited by 69 · see citing works
Beldhuis, I. E., Marapin, R. S., Jiang, Y. Y., Simões de Souza, N. F., Georgiou, A., Kaufmann, T., Castela Forte, J., & van der Horst, I. C. C. (2021) · Journal of Critical Care · doi:10.1016/j.jcrc.2021.04.012 · Cited by 58 · see citing works
Recognizing and reducing cognitive bias in clinical and forensic neurology
Satya-Murti, S., & Lockhart, J. (2015) · Neurology Clinical Practice · doi:10.1212/cpj.0000000000000181 · Cited by 42 · see citing works
Cognitive bias and decision aid use under stressful conditions
Phillips-Wren, G., Jefferson, T., & McKniff, S. (2019) · Journal of Decision Systems · doi:10.1080/12460125.2019.1643695 · Cited by 22 · see citing works
A Cognitive Autopsy Approach Towards Explaining Diagnostic Failure
Croskerry, P., & Campbell, S. G. (2021) · Cureus · doi:10.7759/cureus.17041 · Cited by 14 · see citing works
Self-citationYager, J., Ritvo, A. D., & MacPhee, E. R. (2022) · Journal of Nervous & Mental Disease · doi:10.1097/nmd.0000000000001548 · Cited by 7 · see citing works
Mastrianni, A., Kim, M. S., Sullivan, T. M., Sippel, G. J., Burd, R. S., Gajos, K. Z., & Sarcevic, A. (2025) · Proceedings of the ACM on Human-Computer Interaction · doi:10.1145/3757512 · Cited by 6 · see citing works
“Providing information synthesis and recommendations improved the decision making of our study participants compared to no AI support.”
Yazdanpanah, A., Jung, H., Soltani, A., & Wager, T. D. (2026) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.2513856123 · Cited by 1 · see citing works
Physicians’ Implicit and Explicit Attitudes About Race by MD Race, Ethnicity, and Gender
Sabin, J. A., Nosek, B. A., Greenwald, A. G., & Rivara, F. P. (2009) · Journal of Health Care for the Poor and Underserved · doi:10.1353/hpu.0.0185 · Cited by 472 · see citing works
- Authors
- Croskerry, P.
- Affiliations
- Dalhousie University (CA)
- Corresponding author
- Croskerry, Pat
- ORCID
- Croskerry, Pat
- Venue
- Academic Emergency Medicine
- Publisher
- Wiley
- Published
- 2002-11
- Volume
- 9
- Issue
- 11
- Pages
- 1184-1204
- ISSN
- 1069-6563 (ISSN-L)
- 1553-2712
- OpenAlex
- W1964143014
- Cited by
- 938
- References
- 8
- Citations by year
- 2026: 42 · 2025: 50 · 2024: 42 · 2023: 44 · 2022: 50 · 2021: 61 · 2020: 86 · 2019: 76 · 2018: 58 · 2017: 44 · 2016: 43 · 2015: 36 · 2014: 46 · 2013: 46 · 2012: 40
- FWCI
- 6.33
- Type
- journal article
- Language
- en
- Open access
- closed
- Locations
- Academic Emergency Medicine (publishedVersion)
- PubMed (publishedVersion)
- Topics
- Health Sciences › Medicine › Family Practice › Clinical Reasoning and Diagnostic Skills
- Social Sciences › Decision Sciences › General Decision Sciences › Decision-Making and Behavioral Economics
- Health Sciences › Medicine › Emergency Medicine › Emergency and Acute Care Studies
- Keywords
- clinical decision-making, cognitive biases, heuristics, cognitive debiasing, emergency medicine, cognitive errors, emergency department, decision strategies
- MeSH terms
- Decision Making, Emergency Medical Services, Emergency Service, Hospital, Humans, Judgment, Pattern Recognition, Automated, Quality of Health Care
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