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First published September 23, 2002 as JAMIA PrePrint; doi:10.1197/jamia.M1123
Journal of the American Medical Informatics Association 2003;10(1):39-51
© 2003 American Medical Informatics Association

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Submitted on March 14, 2002
Accepted on August 28, 2002

Development of Visual Diagnostic Expertise in Pathology- An Information-Processing Study

Rebecca S. Crowley MD, MS1*, Gregory J. Naus MD2, Jimmie Stewart III MD3, and Charles P. Friedman PhD4

Affiliation of the authors: 1 Center for Pathology Informatics, Center for Biomedical Informatics, Department of Pathology, University of Pittsburgh School of Medicine, Pittsburgh, PA; 2 Department of Pathology, University of Pittsburgh School of Medicine, Pittsburgh, PA; 3 Department of Pathology and Laboratory, University of Kentucky Medical Center, Lexington, KY; 4 Center for Biomedical Informatics, University of Pittsburgh School of Medicine, Pittsburgh, PA

* To whom correspondence should be addressed.

Objective Identify key features contributing to trainees' development of expertise in microscopic pathology diagnosis, a complex visual task. Provide new insights to help create computer-based training systems in Pathology.

Design Standard methods of information-processing and cognitive science were used to study diagnostic processes (search, perception, reasoning) of 28 novices, intermediates and experts. Participants examined cases in breast pathology; each case had a previously established gold standard diagnosis. Videotapes correlated the actual visual data examined by participants with their verbal think-aloud protocols.

Measurements Investigators measured accuracy, difficulty, certainty, protocol process frequencies, error frequencies, and times to key diagnostic events for each case and subject. Analyses of Variance, Chi-Square tests and post-hoc comparisons were performed with subject as the unit of analysis.

Results Level of expertise corresponded with differences in search, perception, and reasoning components of the tasks. Several discrete steps occur on the path to competence, including: development of adequate search strategies, rapid and accurate recognition of anatomic location, acquisition of visual data interpretation skills, and transitory reliance on explicit feature identification.

Conclusion Results provide the basis for an empirical cognitive model of competence for the complex tasks of microscopic pathology diagnosis. Results will inform the development of computer-based pedagogy tools in this domain.




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