Cognitive biases in surgery: systematic review
Executive Summary
Cognitive biases (CBs)—defined as systematic errors in thinking—are significant contributors to preventable adverse events in surgical care. This briefing document synthesizes the findings of a comprehensive systematic review involving 39 studies, 6,514 surgeons, and over 200,000 patients. The review identifies 31 distinct types of cognitive bias, with overconfidence, anchoring, and confirmation bias being the most prevalent.
Critical findings include:
Performance Impact: Cognitive biases influence six core themes of surgical performance, most notably risk-benefit estimations and perceptions of ability.
Patient Outcomes: Biases are directly linked to actual patient harm, including surgical "never events" (e.g., wrong-site surgery), increased complications, and patient death.
Research Gaps: The majority of existing research focuses on the preoperative phase and hypothetical scenarios. There is a critical lack of empirical research regarding the sources of these biases and the effectiveness of mitigation strategies.
Mitigation Limitations: While education is frequently suggested to increase awareness, evidence suggests that awareness alone does not reduce susceptibility to bias in clinical practice.
Overview of Cognitive Biases in Surgery
The literature identifies 31 types of cognitive bias affecting surgeons. These biases occur across all phases of care, though they are most frequently studied in the preoperative phase.
Most Prevalent Biases
Distribution Across Surgical Phases
Preoperative (53%): Primarily affects diagnosis and treatment planning.
Intraoperative (28%): Influences technical performance and real-time decision-making.
Postoperative (8%): Affects complication management and prognosis estimations.
Thematic Analysis of Impact on Surgical Performance
Cognitive biases differentially influence surgical performance across six identified themes:
1. Inaccurate Risk–Benefit Estimations
Surgeons often struggle to accurately estimate the effectiveness of interventions or the probability of complications.
Examples: Overestimating the success of surgical interventions; inconsistent risk estimation when data is presented in absolute values versus percentages (denominator neglect).
Associated Biases: Anchoring, overconfidence, representativeness, and risk aversion.
2. Inaccurate Perceptions of Ability
This theme involves surgeons overestimating their skills or the quality of their patient outcomes compared to peers.
Key Finding: Overconfidence is the primary driver here. For instance, some surgeons believe their patient outcomes are superior to others regardless of objective data.
Impact: Can lead to "risk-seeking" behavior, which has been linked to patient injury and death.
3. Variation in Risk Tolerance
Subjective risk tolerance affects clinical decisions, often driven by recent personal experiences.
Recency Effect: Surgeons who recently experienced a negative outcome (e.g., an anastomotic leak) may become more risk-averse in subsequent operations, potentially increasing operating room times for additional testing.
4. Not Considering Alternative Options
Biases can cause surgeons to accept a diagnosis or treatment plan prematurely without critical consideration of alternatives.
Evidence: In one study, 82% of surgical "never events" were attributed to confirmation bias.
Impact: Leads to delayed diagnoses, overtreatment, and failure to run necessary tests.
5. Inconsistent Treatment Recommendations
Surgeons may recommend different treatments for patients than they would choose for themselves under identical clinical conditions.
Experience Bias: Surgeons may weigh patient demographic information (irrelevant to clinical needs) differently when making recommendations.
6. Heterogeneous Impacts ("Other")
A variety of other biases, such as insurance bias (providing different care levels based on insurance status) and planning fallacy (underestimating operating room time), also affect surgical care.
Impact on Patient Outcomes
The review distinguishes between actual observed outcomes and predicted potential outcomes.
Actual Patient Harm
Potential Patient Harm
Research suggests biases create significant potential for:
Unnecessary diagnostic tests and overtreatment.
Unrealistic patient expectations regarding pain relief and recovery.
Increased patient anxiety due to inaccurate time management (planning fallacy).
Sources and Mitigation Strategies
Potential Sources
While no studies have empirically investigated the sources of cognitive bias in surgery, the literature suggests two categories:
Person-Based: Most authors attribute bias to individual factors, particularly experience level. However, the relationship is complex; both novices and experts are susceptible to different types of bias.
System-Based: Only one study identified institutional pressure (e.g., pressure to finish procedures quickly) as a source that triggers biases like anchoring and commission bias.
Suggested Mitigation
There is a notable absence of implemented and tested mitigation strategies in surgical literature.
Education: The most common suggestion is using education to increase awareness. However, the review notes that awareness does not necessarily translate to reduced susceptibility.
System Changes: The review suggests that "nudges" or system-level changes—such as prompts for surgeons to recall past complications or "speak-up" campaigns to encourage alternative viewpoints—may be more effective than education alone.
Conclusion
Cognitive biases are an omnipresent threat to surgical safety, contributing to misdiagnosis, technical errors, and adverse patient outcomes. While overconfidence, anchoring, and confirmation bias are the most documented, the field is in its infancy, with over 180 known cognitive biases yet to be fully explored in a surgical context. Future research must shift from identifying biases in hypothetical settings to empirically investigating their work-system sources and testing robust, system-level mitigation strategies.
