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A decision analytic method for scoring performance on computer-based patient simulations

S M Downs1, C P Friedman, F Marasigan

  • 1University of North Carolina at Chapel Hill, USA.

Proceedings : a Conference of the American Medical Informatics Association. AMIA Fall Symposium
|January 1, 1997
PubMed
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A new decision analytic approach scores performance in computerized patient case simulations. This method evaluates data requests, distinguishing serious from minor misdiagnoses for better clinical training.

Area of Science:

  • Medical Education Technology
  • Clinical Decision Making
  • Infectious Disease Simulation

Background:

  • Computer-based clinical case simulations are increasingly used for clinician training and evaluation.
  • Effective methods are needed to assess trainee performance in solving these simulated cases.
  • Existing evaluation approaches may not adequately capture the nuances of diagnostic reasoning.

Purpose of the Study:

  • To develop and present a decision analytic approach for scoring performance on computerized patient case simulations.
  • To create decision models for infectious disease simulations using influence diagrams.
  • To establish a normative measure for evaluating the quality of clinical data requests during simulations.

Main Methods:

  • Developed decision models represented as influence diagrams for four infectious disease domains.

Related Experiment Videos

  • Incorporated nodes for diagnoses, competing disease probabilities, and utilities.
  • Calculated the expected value of information (VOI) for each data request to assess its quality relative to perfect information.

    • Main Results:

    • The approach provides a continuous, sensitive measure of data request quality based on collected information.
    • The scoring method effectively distinguishes between serious and minor misdiagnoses.
    • A single influence diagram can evaluate performance across multiple simulations within the same clinical domain.

    Conclusions:

    • The decision analytic approach offers a robust and objective method for evaluating performance in clinical case simulations.
    • This scoring system enhances the utility of simulations for training and assessment by providing detailed feedback on diagnostic strategies.
    • The methodology is adaptable and applicable to various clinical domains requiring diagnostic reasoning.