scholarly journals P139: How available is availability bias? Examining factors that influence diagnostic error

CJEM ◽  
2018 ◽  
Vol 20 (S1) ◽  
pp. S106-S106
Author(s):  
J. Sherbino ◽  
S. Monteiro ◽  
J. Ilgen ◽  
E. Hayden ◽  
E. Howey ◽  
...  

Introduction: Cognitive bias is often cited as an explanation for diagnostic errors. Of the numerous cognitive biases currently discussed in the literature, availability bias, defined as the current case reminds you of a recent similar example is most well-known. Despite the ubiquity of cognitive biases in medical and popular literature, there is surprisingly little evidence to substantiate these claims. The present study sought to measure the influence of availability bias and identify contributing factors that may increase susceptibility to the influence of a recent similar case. Methods: To investigate the role of prior examples and category priming on diagnostic error at different levels of expertise, we devised a 2 phase experiment. The experimental intervention was in a validation phase preceding the test, where participants were asked to verify a diagnosis which was either i) representative of Diagnosis A, and similar to a test case, ii) representative of Diagnosis A and dissimilar to a test case, iii) representative of Diagnosis B and similar to a test case. The test phase consisted of 8 written cases, each with two approximately equally likely diagnoses(A or B). Each participant verified 2 cases from each condition, for a total of 6. They then diagnosed all 8 test cases; the remaining 2 test cases had no prior example. All cases were counterbalanced across conditions. Comparison between Condition i) and ii) and no prior showed effect of prior exemplar; comparison between iii) and no prior showed effect of category priming. Because cases were designed so that both Diagnosis A and B were likely, overall accuracy was measured as the sum of proportion of cases in which either was selected. Subjects were emergency medicine staff (n=40), residents (n=39) and medical students (n=32) from McMaster University, University of Washington, and Harvard Medical School. Results: Overall, staff had an accuracy (A + B) of 98%, residents 98% and students 85% (F=35.6,p<.0001). For residents and staff there was no effect of condition (all mean accuracies 97% to 100%); for students there was a clear effect of category priming, with accuracy of 84% for i), 87% for ii) and 94% for iii) but only 73% for the no prime condition (Interaction F= 3.54, p<.002) Conclusion: Although prior research has shown substantial biasing effects of availability, primarily in cases requiring visual diagnosis, the present study has shown such effects only for novices (medical students). Possible explanations need to be explored. Nevertheless, our study shows that with increasing expertise, availability may not be a source of error.

Diagnosis ◽  
2021 ◽  
Vol 0 (0) ◽  
Author(s):  
Vita Jaspan ◽  
Verity Schaye ◽  
Andrew S. Parsons ◽  
David Kudlowitz

Abstract Objectives Cognitive biases can result in clinical reasoning failures that can lead to diagnostic errors. Autobrewery syndrome is a rare, but likely underdiagnosed, condition in which gut flora ferment glucose, producing ethanol. It most frequently presents with unexplained episodes of inebriation, though more case studies are necessary to better characterize the syndrome. Case presentation This is a case of a 41-year old male with a past medical history notable only for frequent sinus infections, who presented with recurrent episodes of acute pancreatitis. In the week prior to his first episode of pancreatitis, he consumed four beers, an increase from his baseline of 1–2 drinks per month. At home, he had several episodes of confusion, which he attributed to fatigue. He underwent laparoscopic cholecystectomy and testing for genetic and autoimmune causes of pancreatitis, which were non-revealing. He was hospitalized 10 more times during that 9-month period for acute pancreatitis with elevated transaminases. During these admissions, he had elevated triglycerides requiring an insulin drip and elevated alcohol level despite abstaining from alcohol for the prior eight months. His alcohol level increased after consumption of complex carbohydrates, confirming the diagnosis of autobrewery syndrome. Conclusions Through integrated commentary on the diagnostic reasoning process, this case underscores how overconfidence can lead to premature closure and anchoring resulting in diagnostic error. Using a metacognitive overview, case discussants describe the importance of structured reflection and a standardized approach to early hypothesis generation to navigate these cognitive biases.


2018 ◽  
Vol 69 (4) ◽  
pp. 409-416 ◽  
Author(s):  
Csilla Egri ◽  
Kathryn E. Darras ◽  
Elena P. Scali ◽  
Alison C. Harris

Peer review for radiologists plays an important role in identifying contributing factors that can lead to diagnostic errors and patient harm. It is essential that all radiologists be aware of the multifactorial causes of diagnostic error in radiology and the methods available to reduce it. This pictorial review provides readers with an overview of common errors that occur in abdominal radiology and strategies to reduce them. This review aims to make readers more aware of pitfalls in abdominal imaging so that these errors can be avoided in the future. This essay also provides a systematic approach to classifying abdominal imaging errors that will be of value to all radiologists participating in peer review.


2021 ◽  
Vol 21 (1) ◽  
Author(s):  
J. Staal ◽  
J. Alsma ◽  
S. Mamede ◽  
A. P. J. Olson ◽  
G. Prins-van Gilst ◽  
...  

Abstract Background Diagnostic errors have been attributed to cognitive biases (reasoning shortcuts), which are thought to result from fast reasoning. Suggested solutions include slowing down the reasoning process. However, slower reasoning is not necessarily more accurate than faster reasoning. In this study, we studied the relationship between time to diagnose and diagnostic accuracy. Methods We conducted a multi-center within-subjects experiment where we prospectively induced availability bias (using Mamede et al.’s methodology) in 117 internal medicine residents. Subsequently, residents diagnosed cases that resembled those bias cases but had another correct diagnosis. We determined whether residents were correct, incorrect due to bias (i.e. they provided the diagnosis induced by availability bias) or due to other causes (i.e. they provided another incorrect diagnosis) and compared time to diagnose. Results We did not successfully induce bias: no significant effect of availability bias was found. Therefore, we compared correct diagnoses to all incorrect diagnoses. Residents reached correct diagnoses faster than incorrect diagnoses (115 s vs. 129 s, p < .001). Exploratory analyses of cases where bias was induced showed a trend of time to diagnose for bias diagnoses to be more similar to correct diagnoses (115 s vs 115 s, p = .971) than to other errors (115 s vs 136 s, p = .082). Conclusions We showed that correct diagnoses were made faster than incorrect diagnoses, even within subjects. Errors due to availability bias may be different: exploratory analyses suggest a trend that biased cases were diagnosed faster than incorrect diagnoses. The hypothesis that fast reasoning leads to diagnostic errors should be revisited, but more research into the characteristics of cognitive biases is important because they may be different from other causes of diagnostic errors.


Diagnosis ◽  
2018 ◽  
Vol 5 (4) ◽  
pp. 257-266
Author(s):  
Mark L. Graber ◽  
Dan Berg ◽  
Welcome Jerde ◽  
Phillip Kibort ◽  
Andrew P.J. Olson ◽  
...  

Abstract This is a case report involving diagnostic errors that resulted in the death of a 15-year-old girl, and commentaries on the case from her parents and involved providers. Julia Berg presented with fatigue, fevers, sore throat and right sided flank pain. Based on a computed tomography (CT) scan that identified an abnormal-appearing gall bladder, and markedly elevated bilirubin and “liver function tests”, she was hospitalized and ultimately underwent surgery for suspected cholecystitis and/or cholangitis. Julia died of unexplained post-operative complications. Her autopsy, and additional testing, suggested that the correct diagnosis was Epstein-Barr virus infection with acalculous cholecystitis. The correct diagnosis might have been considered had more attention been paid to her presenting symptoms, and a striking degree of lymphocytosis that was repeatedly demonstrated. The case illustrates how cognitive “biases” can contribute to harm from diagnostic error. The case has profoundly impacted the involved healthcare organization, and Julia’s parents have become leaders in helping advance awareness and education about diagnostic error and its prevention.


Diagnosis ◽  
2021 ◽  
Vol 0 (0) ◽  
Author(s):  
Charles D. Magee ◽  
Andrew S. Parsons ◽  
Alexander S. Millard ◽  
Dario Torre

Abstract Objectives Defects in human cognition commonly result in clinical reasoning failures that can lead to diagnostic errors. Case presentation A 43-year-old female was brought to the emergency department with 4–5 days of confusion, disequilibrium resulting in several falls, and hallucinations. Further investigation revealed tachycardia, diaphoresis, mydriatic pupils, incomprehensible speech and she was seen picking at the air. Given multiple recent medication changes, there was initial concern for serotonin syndrome vs. an anticholinergic toxidrome. She then developed a fever, marked leukocytosis, and worsening encephalopathy. She underwent lumbar puncture and aspiration of an identified left ankle effusion. Methicillin sensitive staph aureus (MSSA) grew from blood, joint, and cerebrospinal fluid cultures within 18 h. She improved with antibiotics and incision, drainage, and washout of her ankle by orthopedic surgery. Conclusions Through integrated commentary on the diagnostic reasoning process from clinical reasoning experts, this case underscores how multiple cognitive biases can cascade sequentially, skewing clinical reasoning toward erroneous conclusions and driving potentially inappropriate testing and treatment. A fishbone diagram is provided to visually demonstrate the major factors that contributed to the diagnostic error. A case discussant describes the importance of structured reflection, a tool to promote metacognitive analysis, and the application of knowledge organization tools such as illness scripts to navigate these cognitive biases.


Diagnosis ◽  
2018 ◽  
Vol 5 (4) ◽  
pp. 223-227 ◽  
Author(s):  
Rabih Geha ◽  
Robert L. Trowbridge ◽  
Gurpreet Dhaliwal ◽  
Andrew P.J. Olson

Abstract Background: Diagnostic error is a major problem in health care, yet there are few medical school curricula focused on improving the diagnostic process and decreasing diagnostic errors. Effective strategies to teach medical students about diagnostic error and diagnostic safety have not been established. Methods: We designed, implemented and evaluated a virtual patient module featuring two linked cases involving diagnostic errors. Learning objectives developed by a consensus process among medical educators in the Society to Improve Diagnosis in Medicine (SIDM) were utilized. The module was piloted with internal medicine clerkship students at three institutions and with clerkship faculty members recruited from listservs. Participants completed surveys on their experience using the case and a qualitative analysis was performed. Results: Thirty-five medical students and 25 faculty members completed the survey. Most students found the module to be relevant and instructive. Faculty also found the module valuable for students but identified insufficient curricular time as a barrier to implementation. Conclusions: Medical students and faculty found a prototype virtual patient module about the diagnostic process and diagnostic error to be educational.


Diagnosis ◽  
2020 ◽  
Vol 0 (0) ◽  
Author(s):  
Sumner Abraham ◽  
Andrew Parsons ◽  
Brian Uthlaut ◽  
Peggy Plews-Ogan

AbstractDespite the breadth of patient safety initiatives, physicians talking about their mistakes to other physicians is a difficult thing to do. This difficulty may be exacerbated by a limited exposure to how to analyze and discuss mistakes and respond in a productive way. At the University of Virginia, we recognized the importance of understanding cognitive biases for residents in both their clinical and personal professional development. We re-designed our resident led morbidity and mortality (M&M) conference using a model that integrates dual-process theory and metacognition to promote informed reflection and analysis of cognitive diagnostic errors. We believe that structuring M&M in this way builds a culture that encourages reflection together to learn our most difficult diagnostic errors and to engage in where our thought processes went wrong. In slowly building this culture, we hope to inoculate residents with the habits of mind that can best protect them from harmful biases in their clinical reasoning while instilling a culture of self-reflection.


2021 ◽  
Vol 26 (4) ◽  
Author(s):  
Man Zhang ◽  
Bogdan Marculescu ◽  
Andrea Arcuri

AbstractNowadays, RESTful web services are widely used for building enterprise applications. REST is not a protocol, but rather it defines a set of guidelines on how to design APIs to access and manipulate resources using HTTP over a network. In this paper, we propose an enhanced search-based method for automated system test generation for RESTful web services, by exploiting domain knowledge on the handling of HTTP resources. The proposed techniques use domain knowledge specific to RESTful web services and a set of effective templates to structure test actions (i.e., ordered sequences of HTTP calls) within an individual in the evolutionary search. The action templates are developed based on the semantics of HTTP methods and are used to manipulate the web services’ resources. In addition, we propose five novel sampling strategies with four sampling methods (i.e., resource-based sampling) for the test cases that can use one or more of these templates. The strategies are further supported with a set of new, specialized mutation operators (i.e., resource-based mutation) in the evolutionary search that take into account the use of these resources in the generated test cases. Moreover, we propose a novel dependency handling to detect possible dependencies among the resources in the tested applications. The resource-based sampling and mutations are then enhanced by exploiting the information of these detected dependencies. To evaluate our approach, we implemented it as an extension to the EvoMaster tool, and conducted an empirical study with two selected baselines on 7 open-source and 12 synthetic RESTful web services. Results show that our novel resource-based approach with dependency handling obtains a significant improvement in performance over the baselines, e.g., up to + 130.7% relative improvement (growing from + 27.9% to + 64.3%) on line coverage.


Diagnosis ◽  
2020 ◽  
Vol 0 (0) ◽  
Author(s):  
Justin B. Searns ◽  
Manon C. Williams ◽  
Christine E. MacBrayne ◽  
Ann L. Wirtz ◽  
Jan E. Leonard ◽  
...  

AbstractObjectivesFew studies describe the impact of antimicrobial stewardship programs (ASPs) on recognizing and preventing diagnostic errors. Handshake stewardship (HS-ASP) is a novel ASP model that prospectively reviews hospital-wide antimicrobial usage with recommendations made in person to treatment teams. The purpose of this study was to determine if HS-ASP could identify and intervene on potential diagnostic errors for children hospitalized at a quaternary care children’s hospital.MethodsPreviously self-identified “Great Catch” (GC) interventions by the Children’s Hospital Colorado HS-ASP team from 10/2014 through 5/2018 were retrospectively reviewed. Each GC was categorized based on the types of recommendations from HS-ASP, including if any diagnostic recommendations were made to the treatment team. Each GC was independently scored using the “Safer Dx Instrument” to determine presence of diagnostic error based on a previously determined cut-off score of ≤1.50. Interrater reliability for the instrument was measured using a randomized subset of one third of GCs.ResultsDuring the study period, there were 162 GC interventions. Of these, 65 (40%) included diagnostic recommendations by HS-ASP and 19 (12%) had a Safer Dx Score of ≤1.50, (Κ=0.44; moderate agreement). Of those GCs associated with diagnostic errors, the HS-ASP team made a diagnostic recommendation to the primary treatment team 95% of the time.ConclusionsHandshake stewardship has the potential to identify and intervene on diagnostic errors for hospitalized children.


Diagnosis ◽  
2020 ◽  
Vol 7 (3) ◽  
pp. 265-272
Author(s):  
Sandra Monteiro ◽  
Jonathan Sherbino ◽  
Jonathan S. Ilgen ◽  
Emily M. Hayden ◽  
Elizabeth Howey ◽  
...  

AbstractObjectivesDiagnostic reasoning has been shown to be influenced by a prior similar patient case. However, it is unclear whether this process influences diagnostic error rates or whether clinicians at all experience levels are equally susceptible. The present study measured the influence of specific prior exposure and experience level on diagnostic accuracy.MethodsTo create the experience of prior exposure, participants (pre-clerkship medical students, emergency medicine residents, and faculty) first verified diagnoses of clinical vignettes. The influence of prior exposures was measured using equiprobable clinical vignettes; indicating two diagnoses. Participants diagnosed equiprobable cases that were: 1) matched to exposure cases (in one of three conditions: a) similar patient features, similar clinical features; b) dissimilar patient features, similar clinical features; c) similar patient features, dissimilar clinical features), or 2) not matched to any prior case (d) no exposure). A diagnosis consistent with a matched exposure case was scored correct. Cases with no prior exposure had no matched cases, hence validated the equiprobable design.ResultsDiagnosis A represented 47% of responses in condition d, but there was no influence of specific similarity of patient characteristics for Diagnosis A, F(3,712)=7.28, p=0.28 or Diagnosis B, F(3,712)=4.87, p=0.19. When re-scored based on matching both equiprobable diagnoses, accuracy was high, but favored faculty (n=40) 98%, and residents (n=39) 98% over medical students (n=32) 85%, F(2,712)=35.6, p<0.0001. Accuracy for medical students was 84, 87, 94, and 73% for conditions a–d, respectively, interaction F(2,712)=3.55, p<0.002.ConclusionsThe differential diagnosis of pre-clerkship medical students improved with prior exposure, but this was unrelated to specific case or patient features. The accuracy of medical residents and staff was not influenced by prior exposure.


Sign in / Sign up

Export Citation Format

Share Document