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Research in medical problem solving: a review.

Laura E Hardin1

  • 1Mississippi StateUniversity, College of Veterinary Medicine, USA. lhardin@cvm.msstate.edu

Journal of Veterinary Medical Education
|December 4, 2003
PubMed
Summary

This review examines medical problem-solving models and reasoning strategies to understand expert-novice differences. It discusses key models like hypothetico-deductive and illness scripts, and methods for studying cognitive processes in medicine.

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Area of Science:

  • Medical Education
  • Cognitive Science
  • Artificial Intelligence in Medicine

Background:

  • Effective problem-solving is crucial for medical diagnosis and treatment.
  • Understanding cognitive processes differentiates expert and novice medical practitioners.

Purpose of the Study:

  • To review and analyze prominent problem-solving models in the medical domain.
  • To explore reasoning strategies used in medical problem-solving.
  • To identify methods for studying cognitive differences between medical experts and novices.

Main Methods:

  • Review of established problem-solving models (hypothetico-deductive, illness scripts, probabilistic).
  • Analysis of reasoning strategies (forward-backward, broad-narrow).
  • Discussion of research methodologies (simulated patients, stimulated recall, think-aloud, Pathfinder algorithm).

Main Results:

  • Identified key cognitive models and reasoning strategies in medical problem-solving.
  • Highlighted differences in these approaches between experts and novices.
  • Outlined various empirical methods for studying medical cognition.

Conclusions:

  • Problem-solving models and reasoning strategies offer insights into medical expertise.
  • Further research using discussed methods can refine our understanding of clinical cognition.
  • This review provides a framework for evaluating and enhancing medical training and practice.

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