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Henk G Schmidt - One of the best experts on this subject based on the ideXlab platform.
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Specific Disease Knowledge as Predictor of Susceptibility to Availability Bias in Diagnostic Reasoning: a Randomized Controlled Experiment
Journal of General Internal Medicine, 2020Co-Authors: Silvia Mamede, Laura Zwaan, Marco Goeijenbier, Stephanie C. E. Schuit, Marco Antonio Carvalho Filho, Justine Staal, Henk G SchmidtAbstract:Background Bias in Reasoning rather than knowledge gaps has been identified as the origin of most Diagnostic errors. However, the role of knowledge in counteracting bias is unclear. Objective To examine whether knowledge of discriminating features (findings that discriminate between look-alike diseases) predicts susceptibility to bias. Design Three-phase randomized experiment. Phase 1 (bias-inducing): Participants were exposed to a set of clinical cases (either hepatitis-IBD or AMI-encephalopathy). Phase 2 (diagnosis): All participants diagnosed the same cases; 4 resembled hepatitis-IBD, 4 AMI-encephalopathy (but all with different diagnoses). Availability bias was expected in the 4 cases similar to those encountered in phase 1. Phase 3 (knowledge evaluation): For each disease, participants decided (max. 2 s) which of 24 findings was associated with the disease. Accuracy of decisions on discriminating features, taken as a measure of knowledge, was expected to predict susceptibility to bias. Participants Internal medicine residents at Erasmus MC, Netherlands. Main Measures The frequency with which higher-knowledge and lower-knowledge physicians gave biased diagnoses based on phase 1 exposure (range 0–4). Time to diagnose was also measured. Key Results Sixty-two physicians participated. Higher-knowledge physicians yielded to availability bias less often than lower-knowledge physicians (0.35 vs 0.97; p = 0.001; difference, 0.62 [95% CI, 0.28–0.95]). Whereas lower-knowledge physicians tended to make more of these errors on subjected-to-bias than on not-subjected-to-bias cases ( p = 0.06; difference, 0.35 [CI, − 0.02–0.73]), higher-knowledge physicians resisted the bias ( p = 0.28). Both groups spent more time to diagnose subjected-to-bias than not-subjected-to-bias cases ( p = 0.04), without differences between groups. Conclusions Knowledge of features that discriminate between look-alike diseases reduced susceptibility to bias in a simulated setting. Reflecting further may be required to overcome bias, but succeeding depends on having the appropriate knowledge. Future research should examine whether the findings apply to real practice and to more experienced physicians.
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immunising physicians against availability bias in Diagnostic Reasoning a randomised controlled experiment
BMJ Quality & Safety, 2020Co-Authors: Silvia Mamede, Marco Antonio De Carvalhofilho, Rosa Malena Delbone De Faria, Daniel Franci, Maria Do Patrocinio Tenorio Nunes, Ligia Maria Cayres Ribeiro, Julia Biegelmeyer, Laura Zwaan, Henk G SchmidtAbstract:Background Diagnostic errors have often been attributed to biases in physicians’ Reasoning. Interventions to ‘immunise’ physicians against bias have focused on improving Reasoning processes and have largely failed. Objective To investigate the effect of increasing physicians’ relevant knowledge on their susceptibility to availability bias. Design, settings and participants Three-phase multicentre randomised experiment with second-year internal medicine residents from eight teaching hospitals in Brazil. Interventions Immunisation: Physicians diagnosed one of two sets of vignettes (either diseases associated with chronic diarrhoea or with jaundice) and compared/contrasted alternative diagnoses with feedback. Biasing phase (1 week later): Physicians were biased towards either inflammatory bowel disease or viral hepatitis. Diagnostic performance test: All physicians diagnosed three vignettes resembling inflammatory bowel disease, three resembling hepatitis (however, all with different diagnoses). Physicians who increased their knowledge of either chronic diarrhoea or jaundice 1 week earlier were expected to resist the bias attempt. Main outcome measurements Diagnostic accuracy, measured by test score (range 0–1), computed for subjected-to-bias and not-subjected-to-bias vignettes diagnosed by immunised and not-immunised physicians. Results Ninety-one residents participated in the experiment. Diagnostic accuracy differed on subjected-to-bias vignettes, with immunised physicians performing better than non-immunised physicians (0.40 vs 0.24; difference in accuracy 0.16 (95% CI 0.05 to 0.27); p=0.004), but not on not-subjected-to-bias vignettes (0.36 vs 0.41; difference −0.05 (95% CI −0.17 to 0.08); p=0.45). Bias only hampered non-immunised physicians, who performed worse on subjected-to-bias than not-subjected-to-bias vignettes (difference −0.17 (95% CI −0.28 to −0.05); p=0.005); immunised physicians’ accuracy did not differ (p=0.56). Conclusions An intervention directed at increasing knowledge of clinical findings that discriminate between similar-looking diseases decreased physicians’ susceptibility to availability bias, reducing Diagnostic errors, in a simulated setting. Future research needs to examine the degree to which the intervention benefits other disease clusters and performance in clinical practice. Trial registration number 68745917.1.1001.0068.
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constructivist problem based learning does work a meta analysis of curricular comparisons involving a single medical school
Educational Psychologist, 2009Co-Authors: Henk G Schmidt, Henk T Van Der Molen, Wilco Te Winkel, Wynand WijnenAbstract:Effects of problem-based learning as reported in curricular comparison studies have been shown to be inconsistent over different medical schools. Therefore, we decided to summarize effects of a single well-established problem-based curriculum rather than to add up sometimes-conflicting findings from different problem-based curricula. Effect sizes were computed for 270 comparisons. The results suggest that students and graduates from the particular curriculum perform much better in the area of interpersonal skills, and with regard to practical medical skills. In addition, they consistently rate the quality of the curriculum as higher. Moreover, fewer students drop out, and those surviving need less time to graduate. Differences with respect to medical knowledge and Diagnostic Reasoning were on average positive but small. These outcomes are at variance with expectations voiced in recent contributions to the literature. They demonstrate that constructivist curricula can have positive effects on learning even...
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the role of basic science knowledge and clinical knowledge in Diagnostic Reasoning a structural equation modeling approach
Academic Medicine, 2005Co-Authors: Anique B H De Bruin, Henk G Schmidt, Remy M J P RikersAbstract:AbstractPurposeTo examine four theories on the role of basic science knowledge and clinical knowledge in Diagnostic Reasoning.MethodIn 2000–01, the authors tested the basic science and clinical knowledge and Diagnostic performances of 59 family physicians and 184 second- to sixth-year medical studen
Geoffrey R Norman - One of the best experts on this subject based on the ideXlab platform.
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effect of teaching bayesian methods using learning by concept vs learning by example on medical students ability to estimate probability of a diagnosis a randomized clinical trial
JAMA Network Open, 2019Co-Authors: John E Brush, Mark Lee, Jonathan Sherbino, Judith C Taylorfishwick, Geoffrey R NormanAbstract:Importance Clinicians use probability estimates to make a diagnosis. Teaching students to make more accurate probability estimates could improve the Diagnostic process and, ultimately, the quality of medical care. Objective To test whether novice clinicians can be taught to make more accurate bayesian revisions of Diagnostic probabilities using teaching methods that apply either explicit conceptual instruction or repeated examples. Design, Setting, and Participants A randomized clinical trial of 2 methods for teaching bayesian updating and Diagnostic Reasoning was performed. A web-based platform was used for consent, randomization, intervention, and testing of the effect of the intervention. Participants included 61 medical students at McMaster University and Eastern Virginia Medical School recruited from May 1 to September 30, 2018. Interventions Students were randomized to (1) receive explicit conceptual instruction regarding Diagnostic testing and bayesian revision (concept group), (2) exposure to repeated examples of cases with feedback regarding posttest probability (experience group), or (3) a control condition with no conceptual instruction or repeated examples. Main Outcomes and Measures Students in all 3 groups were tested on their ability to update the probability of a diagnosis based on either negative or positive test results. Their probability revisions were compared with posttest probability revisions that were calculated using the Bayes rule and known test sensitivity and specificity. Results Of the 61 participants, 22 were assigned to the concept group, 20 to the experience group, and 19 to the control group. Approximate age was 25 years. Two participants were first-year; 37, second-year; 12, third-year; and 10, fourth-year students. Mean (SE) probability estimates of students in the concept group were statistically significantly closer to calculated bayesian probability than the other 2 groups (concept, 0.4%; [0.7%]; experience, 3.5% [0.7%]; control, 4.3% [0.7%];P Conclusions and Relevance The study showed a modest advantage for students who received theoretical instruction on bayesian concepts. All participants’ probability estimates were, on average, close to the bayesian calculation. These findings have implications for how to teach Diagnostic Reasoning to novice clinicians. Trial Registration ClinicalTrials.gov identifier:NCT04130607
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disrupting Diagnostic Reasoning do interruptions instructions and experience affect the Diagnostic accuracy and response time of residents and emergency physicians
Academic Medicine, 2015Co-Authors: Sandra Monteiro, Jonathan S Ilgen, Jonathan Sherbino, Kelly Dore, Timothy J Wood, Meredith Young, Glen Bandiera, Danielle Blouin, Wolfgang Gaissmaier, Geoffrey R NormanAbstract:PurposeOthers have suggested that increased time pressure, sometimes caused by interruptions, may result in increased Diagnostic errors. The authors previously found, however, that increased time pressure alone does not result in increased errors, but they did not test the effect of interruptions. I
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ineffectiveness of cognitive forcing strategies to reduce biases in Diagnostic Reasoning a controlled trial
Canadian Journal of Emergency Medicine, 2014Co-Authors: Jonathan Sherbino, Kulamakan Kulasegaram, Elizabeth Howey, Geoffrey R NormanAbstract:OBJECTIVES Cognitive forcing strategies (CFS) may reduce error arising from cognitive biases. This is the first experimental test to determine the effect of CFS training in medical students. METHODS Students were allocated to CFS training or control during a 4-week emergency medicine rotation (n = 191). At the end of the rotation examination, students were tested using computer-based cases. Application of CFS could enable reduction of Diagnostic error, as evidenced by identifying multiple correct diagnoses for the two cases prone to search satisficing bias (SSB) and uncommon diagnoses for the two cases prone to availability bias (AB). Two "false positive" cases were included to test for possible "oversearching." RESULTS There were 145 students in the intervention and 46 in the control group. For the SSB cases, 52% of students with CFS training and 48% in the control group initiated a search for the second diagnosis (χ2 = 0.13, df = 1, p = 0.91). More than half (54%) correctly identified the second diagnosis in the CFS group, and 48% identified it in the control group. The difference was not significant (χ2 = 2.25, df = 1, p = 0.13). For the second diagnosis in the false positive cases, 64% of the CFS group and 77% of the control group incorrectly identified it. There were no significant differences between groups (χ2 = 2.38, df = 1, p = 0.12). In the AB cases, only 45% in each group identified the uncommon correct diagnosis (χ2 = 0.001, df = 1, p = 0.98). CONCLUSIONS The educational interventions suggested by experts in clinical Reasoning and employed in our study to teach CFS failed to show any reduction in Diagnostic error by novices.
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building on experience the development of clinical Reasoning
The New England Journal of Medicine, 2006Co-Authors: Geoffrey R NormanAbstract:As medical students become physicians, they need to learn to diagnose and manage clinical problems — a process often referred to as developing clinical Reasoning skills. Researchers have been exploring the nature of clinical Diagnostic Reasoning for more than three decades. The initial interest was sparked by a new generation of medical schools, such as those at McMaster University and Michigan State University, whose curricula were explicitly directed toward teaching and learning about “clinical problem-solving.” Little was known about the process, but the belief was that if it were better understood, we could teach it more effectively. In this issue . . .
Silvia Mamede - One of the best experts on this subject based on the ideXlab platform.
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Specific Disease Knowledge as Predictor of Susceptibility to Availability Bias in Diagnostic Reasoning: a Randomized Controlled Experiment
Journal of General Internal Medicine, 2020Co-Authors: Silvia Mamede, Laura Zwaan, Marco Goeijenbier, Stephanie C. E. Schuit, Marco Antonio Carvalho Filho, Justine Staal, Henk G SchmidtAbstract:Background Bias in Reasoning rather than knowledge gaps has been identified as the origin of most Diagnostic errors. However, the role of knowledge in counteracting bias is unclear. Objective To examine whether knowledge of discriminating features (findings that discriminate between look-alike diseases) predicts susceptibility to bias. Design Three-phase randomized experiment. Phase 1 (bias-inducing): Participants were exposed to a set of clinical cases (either hepatitis-IBD or AMI-encephalopathy). Phase 2 (diagnosis): All participants diagnosed the same cases; 4 resembled hepatitis-IBD, 4 AMI-encephalopathy (but all with different diagnoses). Availability bias was expected in the 4 cases similar to those encountered in phase 1. Phase 3 (knowledge evaluation): For each disease, participants decided (max. 2 s) which of 24 findings was associated with the disease. Accuracy of decisions on discriminating features, taken as a measure of knowledge, was expected to predict susceptibility to bias. Participants Internal medicine residents at Erasmus MC, Netherlands. Main Measures The frequency with which higher-knowledge and lower-knowledge physicians gave biased diagnoses based on phase 1 exposure (range 0–4). Time to diagnose was also measured. Key Results Sixty-two physicians participated. Higher-knowledge physicians yielded to availability bias less often than lower-knowledge physicians (0.35 vs 0.97; p = 0.001; difference, 0.62 [95% CI, 0.28–0.95]). Whereas lower-knowledge physicians tended to make more of these errors on subjected-to-bias than on not-subjected-to-bias cases ( p = 0.06; difference, 0.35 [CI, − 0.02–0.73]), higher-knowledge physicians resisted the bias ( p = 0.28). Both groups spent more time to diagnose subjected-to-bias than not-subjected-to-bias cases ( p = 0.04), without differences between groups. Conclusions Knowledge of features that discriminate between look-alike diseases reduced susceptibility to bias in a simulated setting. Reflecting further may be required to overcome bias, but succeeding depends on having the appropriate knowledge. Future research should examine whether the findings apply to real practice and to more experienced physicians.
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immunising physicians against availability bias in Diagnostic Reasoning a randomised controlled experiment
BMJ Quality & Safety, 2020Co-Authors: Silvia Mamede, Marco Antonio De Carvalhofilho, Rosa Malena Delbone De Faria, Daniel Franci, Maria Do Patrocinio Tenorio Nunes, Ligia Maria Cayres Ribeiro, Julia Biegelmeyer, Laura Zwaan, Henk G SchmidtAbstract:Background Diagnostic errors have often been attributed to biases in physicians’ Reasoning. Interventions to ‘immunise’ physicians against bias have focused on improving Reasoning processes and have largely failed. Objective To investigate the effect of increasing physicians’ relevant knowledge on their susceptibility to availability bias. Design, settings and participants Three-phase multicentre randomised experiment with second-year internal medicine residents from eight teaching hospitals in Brazil. Interventions Immunisation: Physicians diagnosed one of two sets of vignettes (either diseases associated with chronic diarrhoea or with jaundice) and compared/contrasted alternative diagnoses with feedback. Biasing phase (1 week later): Physicians were biased towards either inflammatory bowel disease or viral hepatitis. Diagnostic performance test: All physicians diagnosed three vignettes resembling inflammatory bowel disease, three resembling hepatitis (however, all with different diagnoses). Physicians who increased their knowledge of either chronic diarrhoea or jaundice 1 week earlier were expected to resist the bias attempt. Main outcome measurements Diagnostic accuracy, measured by test score (range 0–1), computed for subjected-to-bias and not-subjected-to-bias vignettes diagnosed by immunised and not-immunised physicians. Results Ninety-one residents participated in the experiment. Diagnostic accuracy differed on subjected-to-bias vignettes, with immunised physicians performing better than non-immunised physicians (0.40 vs 0.24; difference in accuracy 0.16 (95% CI 0.05 to 0.27); p=0.004), but not on not-subjected-to-bias vignettes (0.36 vs 0.41; difference −0.05 (95% CI −0.17 to 0.08); p=0.45). Bias only hampered non-immunised physicians, who performed worse on subjected-to-bias than not-subjected-to-bias vignettes (difference −0.17 (95% CI −0.28 to −0.05); p=0.005); immunised physicians’ accuracy did not differ (p=0.56). Conclusions An intervention directed at increasing knowledge of clinical findings that discriminate between similar-looking diseases decreased physicians’ susceptibility to availability bias, reducing Diagnostic errors, in a simulated setting. Future research needs to examine the degree to which the intervention benefits other disease clusters and performance in clinical practice. Trial registration number 68745917.1.1001.0068.
Sally Kennedy - One of the best experts on this subject based on the ideXlab platform.
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teaching dual process Diagnostic Reasoning to doctor of nursing practice students problem based learning and the illness script
Journal of Nursing Education, 2014Co-Authors: Catherine O Durham, Terri Fowler, Sally KennedyAbstract:Accelerating the development of Diagnostic Reasoning skills for nurse practitioner students is high on the wish list of many faculty. The purpose of this article is to describe how the teaching strategy of problem-based learning (PBL) that drills the hypothetico-deductive or analytic Reasoning process when combined with an assignment that fosters pattern recognition (a nonanalytic process) teaches and reinforces the dual process of Diagnostic Reasoning. In an online Doctor of Nursing Practice program, four PBL cases that start with the same symptom unfold over 2 weeks. These four cases follow different paths as they unfold leading to different diagnoses. Culminating each PBL case, a unique assignment called an illness script was developed to foster the development of pattern recognition. When combined with hypothetico-deductive Reasoning drilled during the PBL case, students experience the dual process approach to Diagnostic Reasoning used by clinicians.
Jin H Kim - One of the best experts on this subject based on the ideXlab platform.
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an integration of heuristic and model based Reasoning in fault diagnosis
Engineering Applications of Artificial Intelligence, 1993Co-Authors: Jong Man Lee, Jin H KimAbstract:Abstract A human expert utilizes various pieces of Diagnostic knowledge very dynamically in problem solving. Recently a few integrated Reasoning systems have been proposed to use various types of knowledge in an integrated way, but they have shortcomings in Reasoning control and Reasoning interactions. To overcome these shortcomings, a Diagnostic Reasoning system with dynamic interactions that uses diverse types of knowledge with cooperation is proposed. The integrated Diagnostic Reasoning system contains heuristic and model-based Reasoning modes. A type of knowledge in one Reasoning mode is shared with another via transformation knowledge. In the integrated Diagnostic Reasoning system, the heuristic Reasoning mode plays a major role in Reasoning, and the model-based one fills the gaps in the heuristic Reasoning mode. The model-based Reasoning mode helps the heuristic one by supporting primitive-level testing, and by generating symptoms and hypotheses. In addition, it undertakes the remaining tasks if the heuristic Reasoning mode fails. The heuristic Reasoning mode, also, aids the model-based one by pruning the candidate set. By applying the integrated Reasoning system to diagnosis of a computer printer circuit the system is shown to be appropriate for the domain that calls for the cooperative use of heuristic and detailed system description knowledge. With the criteria of efficiency and coverage, it has been shown that the proposed system is appropriate when insufficient symptoms and heuristic rules are provided.