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Updated: Sep 22, 2025

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CDS-Compare: A Web Application for Machine Learning Assisted Curation of Clinical Order Sets.

Zackary Falls1, Steven H Brown2,3, Naveed Shah1

  • 1Department of Biomedical Informatics, Jacobs School of Medicine and Biomedical Sciences, University at Buffalo, USA.

Studies in Health Technology and Informatics
|May 25, 2022
PubMed
Summary

Developing clinical decision support (CDS) order sets improves care, but curation is challenging. Our CDS-Compare software uses clustering to streamline the review of large order set databases, enhancing efficiency and consistency for expert reviewers.

Keywords:
Clinical Decision SupportDatabase CurationMachine LearningOrder sets

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Area of Science:

  • Health Informatics
  • Clinical Decision Support
  • Natural Language Processing

Background:

  • Disease-specific order sets enhance clinician efficiency and patient safety.
  • Curating order sets for consistency across multiple healthcare sites is complex and time-consuming.

Purpose of the Study:

  • To introduce CDS-Compare, a novel software tool designed to assist expert reviewers in efficiently curating large databases of clinical decision support order sets.
  • To evaluate the effectiveness of CDS-Compare in validating clustered order sets.

Main Methods:

  • Developed CDS-Compare software utilizing a clustering-based approach.
  • Processed a database of order sets extracted from the Veterans Affairs Electronic Health Record using Natural Language Processing (NLP).
  • Subject-matter experts reviewed the web application interface of CDS-Compare to assess clustering validity.

Main Results:

  • The study successfully applied clustering-based software to a large database of NLP-processed order sets.
  • Expert reviewers assessed the web application version of CDS-Compare for clustering validity.
  • The software aims to reduce the burden on expert reviewers during the order set curation process.

Conclusions:

  • CDS-Compare offers a potential solution for the efficient and effective curation of clinical decision support order sets.
  • The software facilitates consistency in order set management across multiple sites.
  • Further validation by subject-matter experts is crucial for refining the tool.