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The search−inference framework: a proposed strategy for novice clinical problem solving
Author(s) -
Aberegg Scott K,
O’Brien James M,
Lucarelli Maria,
Terry Peter B
Publication year - 2008
Publication title -
medical education
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.776
H-Index - 138
eISSN - 1365-2923
pISSN - 0308-0110
DOI - 10.1111/j.1365-2923.2008.03019.x
Subject(s) - inference , computer science , medline , management science , psychology , machine learning , medical education , artificial intelligence , medicine , engineering , political science , law
Context Medical education in the clinical clerkship years emphasises the systematic collection and organisation of patient information to be combined with domain‐specific knowledge of disease processes. Eventually, novice clinical problem solvers will learn to recognise patterns within the patient data (‘illness scripts’) which suggest the main diagnostic possibilities. Before novice problem solvers develop these illness scripts, pattern recognition may not be effective for solving clinical problems. Methods This discussion paper describes the application of a decision framework adapted from cognitive psychology (the search−inference framework) to basic medical problem solving. Emphasis is placed on problem solving by novices who have not yet developed a full compliment of illness scripts. Conclusions The search−inference framework is similar to the approach taken by laypersons to diagnose their own symptoms or solve other problems. It may be especially useful for students who have not yet developed a sizeable repertoire of illness scripts, and the principles described may also be invoked by experienced clinicians confronting difficult clinical problems.