BACKGROUND: Clinical experience, features of data collection process, or both, affect diagnostic accuracy, but their respective role is unclear. OBJECTIVE, DESIGN: Prospective, observational study, to determine the respective contribution of clinical experience and data collection features to diagnostic accuracy. METHODS: Six Internists, 6 second year internal medicine residents, and 6 senior medical students worked up the same 7 cases with a standardized patient. Each encounter was audiotaped and immediately assessed by the subjects who indicated the reasons underlying their data collection. We analyzed the encounters according to diagnostic accuracy, information collected, organ systems explored, diagnoses evaluated, and final decisions made, and we determined predictors of diagnostic accuracy by logistic regression models. RESULTS: Several features significantly predicted diagnostic accuracy after correction for clinical experience: early exploration of correct diagnosis (odds ratio [OR] 24.35) or of relevant diagnostic hypotheses (OR 2.22) to frame clinical data collection, larger number of diagnostic hypotheses evaluated (OR 1.08), and collection of relevant clinical data (OR 1.19). CONCLUSION: Some features of data collection and interpretation are related to diagnostic accuracy beyond clinical experience and should be explicitly included in clinical training and modeled by clinical teachers. Thoroughness in data collection should not be considered a privileged way to diagnostic success.
BACKGROUND: Clinical experience, features of data collection process, or both, affect diagnostic accuracy, but their respective role is unclear. OBJECTIVE, DESIGN: Prospective, observational study, to determine the respective contribution of clinical experience and data collection features to diagnostic accuracy. METHODS: Six Internists, 6 second year internal medicine residents, and 6 senior medical students worked up the same 7 cases with a standardized patient. Each encounter was audiotaped and immediately assessed by the subjects who indicated the reasons underlying their data collection. We analyzed the encounters according to diagnostic accuracy, information collected, organ systems explored, diagnoses evaluated, and final decisions made, and we determined predictors of diagnostic accuracy by logistic regression models. RESULTS: Several features significantly predicted diagnostic accuracy after correction for clinical experience: early exploration of correct diagnosis (odds ratio [OR] 24.35) or of relevant diagnostic hypotheses (OR 2.22) to frame clinical data collection, larger number of diagnostic hypotheses evaluated (OR 1.08), and collection of relevant clinical data (OR 1.19). CONCLUSION: Some features of data collection and interpretation are related to diagnostic accuracy beyond clinical experience and should be explicitly included in clinical training and modeled by clinical teachers. Thoroughness in data collection should not be considered a privileged way to diagnostic success.
Authors: Mathieu R Nendaz; Anne M Gut; Arnaud Perrier; Olivier Reuille; Martine Louis-Simonet; Alain F Junod; Nu V Vu Journal: Med Educ Date: 2004-01 Impact factor: 6.251
Authors: Ana Suárez; Alberto Adanero; Víctor Díaz-Flores García; Yolanda Freire; Juan Algar Journal: Int J Environ Res Public Health Date: 2022-07-18 Impact factor: 4.614