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Maintaining and incrementally revalidating a computer-based clinical guideline: a case study.

P L Miller1, S J Frawley, F G Sayward

  • 1Center for Medical Informatics, Yale University School of Medicine, P.O. Box 208009, New Haven, CT 06520-8009, USA. perry.miller@yale.edu

Journal of Biomedical Informatics
|August 23, 2001
PubMed
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Maintaining complex computer-based clinical guidelines, like childhood immunization schedules, involves managing national changes and local adaptations. This study details logic issues encountered and proposes domain knowledge for automated validation.

Area of Science:

  • Health Informatics
  • Computer Science
  • Public Health

Background:

  • Computer-based clinical guidelines are essential for healthcare delivery.
  • Maintaining the accuracy and relevance of these guidelines is challenging due to evolving medical recommendations and local healthcare needs.
  • The IMM/Serve system for childhood immunization serves as a practical case study for these challenges.

Purpose of the Study:

  • To explore the complexities of maintaining logic in computer-based clinical guidelines.
  • To document issues arising from national recommendation changes and local system customizations.
  • To investigate the role of domain knowledge in validating guideline logic.

Main Methods:

  • A longitudinal log was maintained for over 1.5 years.

Related Experiment Videos

  • Data collected included national immunization recommendation changes, local IMM/Serve logic customizations, and logic problems encountered.
  • Analysis focused on the nature of these changes, customizations, and problems.

    • Main Results:

    • Significant challenges exist in updating and customizing clinical guideline logic.
    • Specific types of logic problems were identified during the adaptation process.
    • The study highlights the practical difficulties in ensuring guideline accuracy over time.

    Conclusions:

    • Maintaining computer-based clinical guidelines requires robust strategies for managing updates and customizations.
    • Domain knowledge can potentially aid in the automated validation of guideline logic.
    • The findings offer insights into the real-world issues of clinical decision support system maintenance.