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The role of strategy and redundancy in diagnostic reasoning.

ABSTRACT: BACKGROUND:Diagnostic reasoning is a key competence of physicians. We explored the effects of knowledge, practice and additional clinical information on strategy, redundancy and accuracy of diagnosing a peripheral neurological defect in the hand based on sensory examination. METHOD:Using an interactive computer simulation that includes 21 unique cases with seven sensory loss patterns and either concordant, neutral or discordant textual information, 21 3rd year medical students, 21 6th year and 21 senior neurology residents each examined 15 cases over the course of one session. An additional 23 psychology students examined 24 cases over two sessions, 12 cases per session. Subjects also took a seven-item MCQ exam of seven classical patterns presented visually. RESULTS:Knowledge of sensory patterns and diagnostic accuracy are highly correlated within groups (R2 = 0.64). The total amount of information gathered for incorrect diagnoses is no lower than that for correct diagnoses. Residents require significantly fewer tests than either psychology or 6th year students, who in turn require fewer than the 3rd year students (p < 0.001). The diagnostic accuracy of subjects is affected both by level of training (p < 0.001) and concordance of clinical information (p < 0.001). For discordant cases, refutation testing occurs significantly in 6th year students (p < 0.001) and residents (p < 0.01), but not in psychology or 3rd year students. Conversely, there is a stable 55% excess of confirmatory testing, independent of training or concordance. CONCLUSIONS:Knowledge and practice are both important for diagnostic success. For complex diagnostic situations reasoning components employing redundancy seem more essential than those using strategy.

SUBMITTER: Bloch RF

PROVIDER: S-EPMC149359 | biostudies-literature | 2003 Jan

REPOSITORIES: biostudies-literature

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The role of strategy and redundancy in diagnostic reasoning.

Bloch Ralph F RF Hofer Daniel D Feller Sabine S Hodel Maria M

BMC medical education 20030124

<h4>Background</h4>Diagnostic reasoning is a key competence of physicians. We explored the effects of knowledge, practice and additional clinical information on strategy, redundancy and accuracy of diagnosing a peripheral neurological defect in the hand based on sensory examination.<h4>Method</h4>Using an interactive computer simulation that includes 21 unique cases with seven sensory loss patterns and either concordant, neutral or discordant textual information, 21 3rd year medical students, 21 ...[more]

PMID: 12542839

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Project description:BACKGROUND AND OBJECTIVE:Intuition is an important part of human decision-making and can be explained by the dual-process theory where analytical and non-analytical reasoning processes continually interact. These processes can also be identified in physicians' diagnostic reasoning. The valuable role of intuition, including gut feelings, has been shown among general practitioners and nurses, but less is known about its role among hospital specialists. This study focused on the diagnostic reasoning of hospital specialists, how they value, experience and use intuition. DESIGN AND PARTICIPANTS:Twenty-eight hospital specialists in the Netherlands and Belgium participated in six focus groups. The discussions were recorded, transcribed verbatim and thematically coded. A circular and iterative analysis was applied until data saturation was achieved. RESULTS:Despite initial reservations regarding the term intuition, all participants agreed that intuition plays an important role in their diagnostic reasoning process. Many agreed that intuition could guide them, but were cautious not to be misguided. They were especially cautious since intuition does not have probative force, for example, in medicolegal situations. 'On-the-job experience' was regarded as a precondition to relying on intuition. Some participants viewed intuition as non-rational and invalid. All participants said that intuitive hunches must be followed by analytical reasoning. Cultural differences were not found. Both the doctor as a person and his/her specialty were seen as important determinants for using intuition. CONCLUSIONS:Hospital specialists use intuitive elements in their diagnostic reasoning, in line with general human decision-making models. Nevertheless, they appear to disagree more on its role and value than previous research has shown among general practitioners. A better understanding of how to take advantage of intuition, while avoiding pitfalls, and how to develop 'skilled' intuition may improve the quality of hospital specialists' diagnostic reasoning.

Project description:The impact of context on the complex process of clinical reasoning is not well understood. Using situated cognition as the theoretical framework and videos to provide the same contextual "stimulus" to all participants, we examined the relationship between specific contextual factors on diagnostic and therapeutic reasoning accuracy in board certified internists versus resident physicians.Each participant viewed three videotaped clinical encounters portraying common diagnoses in internal medicine. We explicitly modified the context to assess its impact on performance (patient and physician contextual factors). Patient contextual factors, including English as a second language and emotional volatility, were portrayed in the videos. Physician participant contextual factors were self-rated sleepiness and burnout.. The accuracy of diagnostic and therapeutic reasoning was compared with covariates using Fisher Exact, Mann-Whitney U tests and Spearman Rho's correlations as appropriate.Fifteen board certified internists and 10 resident physicians participated from 2013 to 2014. Accuracy of diagnostic and therapeutic reasoning did not differ between groups despite residents reporting significantly higher rates of sleepiness (mean rank 20.45 vs 8.03, U = 0.5, p < .001) and burnout (mean rank 20.50 vs 8.00, U = 0.0, p < .001). Accuracy of diagnosis and treatment were uncorrelated (r = 0.17, p = .65). In both groups, the proportion scoring correct responses for treatment was higher than the proportion scoring correct responses for diagnosis.This study underscores that specific contextual factors appear to impact clinical reasoning performance. Further, the processes of diagnostic and therapeutic reasoning, although related, may not be interchangeable. This raises important questions about the impact that contextual factors have on clinical reasoning and provides insight into how clinical reasoning processes in more authentic settings may be explained by situated cognition theory.

Project description:BackgroundOntology has attracted substantial attention from both academia and industry. Handling uncertainty reasoning is important in researching ontology. For example, when a patient is suffering from cirrhosis, the appearance of abdominal vein varices is four times more likely than the presence of bitter taste. Such medical knowledge is crucial for decision-making in various medical applications but is missing from existing medical ontologies. In this paper, we aim to discover medical knowledge probabilities from electronic medical record (EMR) texts to enrich ontologies. First, we build an ontology by identifying meaningful entity mentions from EMRs. Then, we propose a symptom-dependency-aware naïve Bayes classifier (SDNB) that is based on the assumption that there is a level of dependency among symptoms. To ensure the accuracy of the diagnostic classification, we incorporate the probability of a disease into the ontology via innovative approaches.ResultsWe conduct a series of experiments to evaluate whether the proposed method can discover meaningful and accurate probabilities for medical knowledge. Based on over 30,000 deidentified medical records, we explore 336 abdominal diseases and 81 related symptoms. Among these 336 gastrointestinal diseases, the probabilities of 31 diseases are obtained via our method. These 31 probabilities of diseases and 189 conditional probabilities between diseases and the symptoms are added into the generated ontology.ConclusionIn this paper, we propose a medical knowledge probability discovery method that is based on the analysis and extraction of EMR text data for enriching a medical ontology with probability information. The experimental results demonstrate that the proposed method can effectively identify accurate medical knowledge probability information from EMR data. In addition, the proposed method can efficiently and accurately calculate the probability of a patient suffering from a specified disease, thereby demonstrating the advantage of combining an ontology and a symptom-dependency-aware naïve Bayes classifier.

Project description:Background. Medical students often have problems with Bayesian reasoning situations. Representing statistical information as natural frequencies (instead of probabilities) and visualizing them (e.g., with double-trees or net diagrams) leads to higher accuracy in solving these tasks. However, double-trees and net diagrams (which already contain the correct solution of the task, so that the solution could be read of the diagrams) have not yet been studied in medical education. This study examined the influence of information format (probabilities v. frequencies) and visualization (double-tree v. net diagram) on the accuracy and speed of Bayesian judgments. Methods. A total of 142 medical students at different university medical schools (Munich, Kiel, Goettingen, Erlangen, Nuremberg, Berlin, Regensburg) in Germany predicted posterior probabilities in 4 different medical Bayesian reasoning tasks, resulting in a 3-factorial 2 × 2 × 4 design. The diagnostic efficiency for the different versions was represented as the median time divided by the percentage of correct inferences. Results. Frequency visualizations led to a significantly higher accuracy and faster judgments than did probability visualizations. Participants solved 80% of the tasks correctly in the frequency double-tree and the frequency net diagram. Visualizations with probabilities also led to relatively high performance rates: 73% in the probability double-tree and 70% in the probability net diagram. The median time for a correct inference was fastest with the frequency double tree (2:08 min) followed by the frequency net diagram and the probability double-tree (both 2:26 min) and probability net diagram (2:33 min). The type of visualization did not result in a significant difference. Discussion. Frequency double-trees and frequency net diagrams help answer Bayesian tasks more accurately and also more quickly than the respective probability visualizations. Surprisingly, the effect of information format (probabilities v. frequencies) on performance was higher in previous studies: medical students seem also quite capable of identifying the correct solution to the Bayesian task, among other probabilities in the probability visualizations.HighlightsFrequency double-trees and frequency nets help answer Bayesian tasks not only more accurately but also more quickly than the respective probability visualizations.In double-trees and net diagrams, the effect of the information format (probabilities v. natural frequencies) on performance is remarkably lower in this high-performing sample than that shown in previous studies.

Project description:PurposeGraduating medical students need broad clinical diagnostic reasoning skills that integrate learning across clinical specialties to deal with undifferentiated patient problems. The opportunity to acquire these skills may be limited during clinical placements on increasingly specialized hospital wards. We developed an intervention of regular general practitioner (GP) facilitated teaching in hospital placements to enable students to develop broad clinical diagnostic reasoning. The intervention was piloted, refined and delivered to a whole cohort of medical students at the start of their third year. This paper examines whether students perceived opportunities to improve their broad diagnostic clinical reasoning through our intervention.MethodsGP-facilitated teaching sessions were delivered weekly in hospital placements to small groups of 6–8 students for 90 mins over 6 weeks. Students practiced clinical reasoning with real patient cases that they encountered on their placements. Evaluation of learning outcomes was conducted through a student questionnaire using Likert scales with free-text boxes for additional explanation. Focus groups were conducted to gain a more in-depth understanding of student perspectives.ResultsAs high as 87% of students agreed that their broad clinical diagnostic reasoning ability had improved. Thematic analysis of the qualitative data revealed four factors supporting this improvement: practicing the hypothetico-deductive method, using real patient cases, composing student groups from different speciality placements and the breadth of the facilitators’ knowledge. Students additionally reported enhanced person-centredness in terms of understanding the patient’s perspective and journey. Students perceived that the added value of general practitioner facilitators lay in their broad knowledge base and knowledge of patient needs in the community.ConclusionOur results suggest that medical students can develop broad clinical diagnostic reasoning skills in hospital settings through regular GP-facilitated teaching. Our approach has the advantage of working within the established curricular format of hospital placements and being deliverable at scale to whole student cohorts.

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The role of strategy and redundancy in diagnostic reasoning.

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The role of strategy and redundancy in diagnostic reasoning.

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