SMALL WORLDS AND MEDICAL EXPERTISE - IMPLICATIONS FOR MEDICAL COGNITION AND KNOWLEDGE ENGINEERING

This paper proposes and defends the small worlds hypothesis, which sta tes that expert physicians organize diagnostic knowledge on the basis of similarities between disease categories, forming 'small worlds' con sisting of small subsets of diseases and their distinguishing features . Examining existing data from several previous studies, the authors p rovide support for the small worlds hypothesis;and for a characterizat ion of the process of expert medical diagnostic reasoning as a success ion of limited comparisons involving related diagnostic hypotheses. In one study, subjects were presented clinical endocrine cases one state ment at a time and were prompted to think aloud after presentation of each statement. A combination of discourse and protocol analysis techn iques were used to investigate hypothesis generation and evaluation. I n another study, dialogues from doctor-patient interviews were examine d. It was found that expert subjects rapidly select relatively small s ets of plausible diagnostic hypotheses (small worlds) and focus on the most relevant medical findings that distinguish among the diseases in such small worlds. Results from both studies indicate that expert phy sicians use efficient strategies for discriminating among these altern ative hypotheses in a stepwise process. In contrast, non-experts often generate large numbers of possible diagnostic hypotheses, belonging t o widely differing disease categories. The results provide empirical s upport for the theoretical basis of small worlds. The implications of these results for the study of medical expertise and knowledge enginee ring are discussed, as well as considerations for the development of d ecision support systems. (C) 1998 Elsevier Science Ireland Ltd. All ri ghts reserved.