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A temporal analysis of QMR

C F Aliferis1, G F Cooper, R A Miller

  • 1Section of Medical Informatics, B50A Lothrop Hall, 190 Lothrop Street, University of Pittsburgh, Pittsburgh, PA, USA. cons@alpha.smi.med.pitt.edu

Journal of the American Medical Informatics Association : JAMIA
|January 1, 1996
PubMed
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The Quick Medical Reference (QMR) diagnostic system implicitly models time. This study found that its abstracted temporal encoding does not negatively impact diagnostic accuracy in internal medicine.

Area of Science:

  • Medical Informatics
  • Artificial Intelligence in Medicine
  • Clinical Decision Support Systems

Background:

  • The Quick Medical Reference (QMR) system, a diagnostic tool in internal medicine, does not explicitly incorporate temporal information.
  • Understanding the trade-offs between expressive power and diagnostic accuracy is crucial for developing effective medical AI.

Purpose of the Study:

  • To evaluate the impact of omitting explicit time representation in the QMR diagnostic system.
  • To assess the relationship between temporal abstractions and diagnostic accuracy in internal medicine.

Main Methods:

  • Phase I involved a descriptive analysis of temporal abstractions within QMR's existing terms.
  • Phase II used a pseudo-prospective controlled experiment analyzing temporal content in patient history, physical exams, and lab results for 105 patients.

Related Experiment Videos

  • Key temporal parameters assessed included primitives, units, uncertainty, processes, and patterns.

    • Main Results:

    • 776 temporal findings were identified within QMR.
    • An ontology was developed to describe QMR's temporal knowledge representation.
    • No statistically significant difference in diagnostic accuracy was observed between high and low temporal complexity cases (OR=0.7, 95% CI=0.27-1.83).

    Conclusions:

    • QMR demonstrates extensive implicit modeling of temporal information.
    • The abstracted encoding of time within QMR's medical knowledge does not appear to penalize its diagnostic performance.