Automated Case Cancellation Review System Improves Systems-Based Practice

Overview

Journal J Med Syst

Specialty Medical Informatics

Date 2015 Aug 31

PMID 26319274

Citations 2

Authors

Joseph R Starnes

Matthew D McEvoy

Jesse M Ehrenfeld

Warren S Sandberg

Jonathan P Wanderer

Affiliations

Soon will be listed here.

Abstract

Background: Accreditation Council for Graduate Medical Education (ACGME) core competencies of systems-based practice and practice-based learning and improvement are difficult to assess, as they are often not directly measurable or observable. Reviewing day-of-surgery cancellations could provide resident learning opportunities in these areas.

Objective: An automated system to facilitate anesthesiology resident review of cancelled cases was implemented on the Preoperative Evaluation Clinic (PEC) rotation at the authors' institution. This study aims to evaluate its impact on resident education.

Methods: Residents on the PEC rotation during the 6 months preceding (n = 22) and following (n = 13) implementation in 2014 were surveyed about their experience performing cancelled case reviews in order to ascertain the effect of the intervention on their training.

Results: Significant changes were reported in the number of cases reviewed by each resident (p < 0.0001), perceived importance of review (p = 0.03), and ease of review (p = 0.03) after system implementation. There was also an increase in the proportion of cancelled cases reviewed from 17.3% (34 of 196) to 95.6% (194 of 203) (p < 0.0001). Non-significant trends were seen in perceived rotation effect on ACGME competencies, including systems-based practice. Several specific improvements to our clinical practice, including the creation of standardized guidelines, arose from these case reviews.

Conclusion: Implementation of automated systems can improve compliance with educational goals by clarifying priorities and simplifying workflow. This system increased the number of cases reviewed by residents and the perceived importance of this review as a part of their educational experience.

Citing Articles

Improving ACGME Compliance for Obstetric Anesthesiology Fellows Using an Automated Email Notification System.

Ende H, Richardson M, Lopez B, Wanderer J Appl Clin Inform. 2021; 12(3):479-483.

PMID: 34041735 PMC: 8154353. DOI: 10.1055/s-0041-1730323.

Visualization of aggregate perioperative data improves anesthesia case planning: A randomized, cross-over trial.

Wanderer J, Lasko T, Coco J, Fowler L, McEvoy M, Feng X J Clin Anesth. 2020; 68:110114.

PMID: 33142248 PMC: 7750268. DOI: 10.1016/j.jclinane.2020.110114.

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