Expertise and error in diagnostic reasoning

Paul E Johnson, Alica S. Durán, Frank Hassebrock, James H Moller, Michael Prietula, Paul J. Feltovich, David B. Swanson

Research output: Contribution to journalArticlepeer-review

164 Scopus citations


An investigation is presented in which a computer simulation model (DIAGNOSER) is used to develop and test predictions for behavior of subjects in a task of medical diagnosis. The first experiment employed a process-tracing methodology in order to compare hypothesis generation and evaluation behavior of DIAGNOSER with individuals at different levels of expertise (students, trainees, experts). A second experiment performed with only DIAGNOSER identified conditions under which errors in reasoning in the first experiment could be related to interpretation of specific data items. Predictions derived from DIAGNOSER's performance were tested in a third experiment with a new sample of subjects. Data from the three experiments indicated that (1) form of diagnostic reasoning was similar for all subjects trained in medicine and for the simulation model, (2) substance of diagnostic reasoning employed by the simulation model was comparable with that of the more expert subjects, and (3) errors in subjects' reasoning were attributable to deficiencies in disease knowledge and the interpretation of specific patient data cues predicted by the simulation model.

Original languageEnglish (US)
Pages (from-to)235-283
Number of pages49
JournalCognitive Science
Issue number3
StatePublished - 1981

Bibliographical note

Funding Information:
*The research reported here has been funded by grants to the fin'st author from (1) the Graduate School at the University of Minnesota, (2) the Center for Research in Human Learning at the University of Minnesota, (3) the National Institute for Child Health and Human Development (T36-HD-07151 and HD-01136), (4) the National Science Foundation (NSFfBNS-77-22075), (5) the University of Minnesota Consulting Group on InstructionalD esign, and (6) the Dwan Family Fund in the University of Minnesota Medical School. Portions of the research were presented to the Sixth Annual Workshop on Artificial Intelligence in Medicine, Stanford University, August, 1980. We would like to express our appreciation to staff and students in the Department of Pediatrics in the University of Minnesota Medical School who have generously given their time and thoughts to this research.


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