Jove
Visualize
Contact Us
JoVE
x logofacebook logolinkedin logoyoutube logo
ABOUT JoVE
OverviewLeadershipBlogJoVE Help Center
AUTHORS
Publishing ProcessEditorial BoardScope & PoliciesPeer ReviewFAQSubmit
LIBRARIANS
TestimonialsSubscriptionsAccessResourcesLibrary Advisory BoardFAQ
RESEARCH
JoVE JournalMethods CollectionsJoVE Encyclopedia of ExperimentsArchive
EDUCATION
JoVE CoreJoVE BusinessJoVE Science EducationJoVE Lab ManualFaculty Resource CenterFaculty Site
Terms & Conditions of Use
Privacy Policy
Policies

Related Experiment Videos

Support for guideline development through error classification and constraint checking.

Mor Peleg1, Vimla L Patel, Vincenza Snow

  • 1Medical Informatics, Stanford University School of Medicine, Stanford, CA, USA.

Proceedings. AMIA Symposium
|December 5, 2002
PubMed
Summary
This summary is machine-generated.

Related Concept Videos

You might also read

Related Articles

Articles linked to this work by shared authors, journal, and citation graph.

Sort by
Same author

Beyond Accuracy: Safety-Centered guidelines for the evaluation of LLM-based therapy recommendation systems for chronic multimorbidity patients.

Journal of biomedical informatics·2026
Same author

Seven deadly sins in artificial intelligence for digital medicine.

NPJ digital medicine·2026
Same author

Epidemiology of invasive meningococcal disease in the United States: review of recent data and identified risk factors.

Frontiers in public health·2026
Same author

Criteria to prioritize clinical practice guideline recommendations for patient decision aid development: results from a modified Delphi consensus study.

Journal of clinical epidemiology·2026
Same author

A data-driven method for research trend analysis in a scientific discipline: Application to the journal of biomedical informatics.

Journal of biomedical informatics·2026
Same author

Lipomas are associated with a higher prevalence of metabolic syndrome components: a multicenter cross-sectional study.

Frontiers in endocrinology·2025
Same journal

Progressive display of very high resolution images using wavelets.

Proceedings. AMIA Symposium·2002
Same journal

The Chronus II temporal database mediator.

Proceedings. AMIA Symposium·2002
Same journal

Gene expression levels in different stages of progression in oral squamous cell carcinoma.

Proceedings. AMIA Symposium·2002
Same journal

An assessment of the visibility of MeSH-indexed medical web catalogs through search engines.

Proceedings. AMIA Symposium·2002
Same journal

Filtering for medical news items using a machine learning approach.

Proceedings. AMIA Symposium·2002
Same journal

Enriching the structure of the UMLS semantic network.

Proceedings. AMIA Symposium·2002
See all related articles

This study analyzed error reduction in clinical algorithm development, recommending procedures and a new tool to improve the creation of computer-interpretable guidelines (CIGs) for better medical practices.

Area of Science:

  • Medical Informatics
  • Clinical Decision Support
  • Health Systems Research

Background:

  • Clinical guidelines are essential for reducing medical errors and practice variation.
  • Computer-interpretable guidelines (CIGs) offer potential for real-time, patient-specific clinical advice.
  • Developing accurate CIGs from narrative guidelines is complex and prone to errors.

Purpose of the Study:

  • To analyze the error progression during the development of clinical algorithms from narrative guidelines.
  • To propose procedural improvements for generating clinical algorithms with fewer errors.
  • To develop and utilize a tool for authoring and validating CIGs in GLIF3 format.

Main Methods:

  • Analysis of changes between successive versions of a clinical algorithm.

Related Experiment Videos

  • Comparison of a narrative guideline with its derived clinical algorithm.
  • Development of a software tool for authoring and validating CIGs based on GLIF3 specifications.
  • Syntax, data type, cardinality, and structural integrity constraint validation using the developed tool.

    • Main Results:

    • Identified specific points of error introduction in the algorithm development process.
    • Demonstrated the utility of the developed authoring and validation tool.
    • Successfully used the tool to author and check clinical guidelines for errors.

    Conclusions:

    • Procedural recommendations can minimize errors in clinical algorithm generation.
    • A dedicated authoring and validation tool enhances the accuracy and reliability of CIGs.
    • Improved CIG development processes contribute to safer and more effective patient care.