Supporting the Episodic Application of Clinical Guidelines over Significant Time Periods

Bruria Ben Shahar, Yuval Shahar, Shai Jaffe, Odeya Cohen, Erez Shalom, Maya Selivanova, Ephraim Rimon, Ayelet Goldstein

Research output: Contribution to journalArticlepeer-review

Abstract

Medical errors contribute significantly to morbidity and mortality, emphasizing the critical role of Clinical Guidelines (GLs) in patient care. Automating GL application can enhance GL adherence, improve patient outcomes, and reduce costs. However, several barriers exist to GL implementation and real-time automated support. Challenges include creating a formalized, machine-comprehensible GL representation, and an episodic decision-support system for sporadic treatment advice. This system must accommodate the non-continuous nature of care delivery, including partial actions or partially met treatment goals. We describe the design and implementation of an episodic GL-based clinical decision support system and its retrospective technical evaluation using patient records from a geriatric center. Initial evaluation scores of the e-Picard system were promising, with a mean 94% correctness and 90% completeness based on 50 random pressure ulcer patients. Errors were mainly due to knowledge specification, algorithmic issues, and missing data. Post-corrections, scores improved to 100% correctness and a mean 97% completeness, with missing data still affecting completeness. The results validate the system's capability to assess guideline adherence and provide quality recommendations. Despite initial limitations, we have demonstrated the feasibility of providing, through the e-Picard episodic algorithm, realistic medical decision-making support for noncontinuous, intermittent consultations.

Original languageEnglish
Pages (from-to)1873-1877
Number of pages5
JournalStudies in Health Technology and Informatics
Volume316
DOIs
StatePublished - 22 Aug 2024

Keywords

  • CDSSs
  • Chronic Patients
  • Clinical Guidelines
  • Episodic support
  • Quality Assessment
  • Quality Assurance

ASJC Scopus subject areas

  • Biomedical Engineering
  • Health Informatics
  • Health Information Management

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