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Automated Case Cancellation Review System Improves Systems-Based Practice

  • Education & Training
  • Published:
Journal of Medical Systems Aims and scope Submit manuscript

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.

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Compliance with Ethical Standards

Funding

Provided by the VUMC Department of Anesthesiology. Additionally, Dr. Wanderer is funded by the Foundation for Anesthesia Education and Research (FAER) and Anesthesia Quality Institute (AQI)’s Health Service Research Mentored Research Training Grant (HSR-MRTG).

Conflicts of Interest

The authors declare that they have no conflict of interest.

Ethical Approval

This study was deemed exempt by the Institutional Review Board at the Vanderbilt University Medical Center.

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Authors and Affiliations

  1. Department of Anesthesiology, Vanderbilt University Medical Center (VUMC), 1301 Medical Center Dr., Nashville, TN, 37232, USA

    Joseph R. Starnes, Matthew D. McEvoy, Jesse M. Ehrenfeld, Warren S. Sandberg & Jonathan P. Wanderer

Authors
  1. Joseph R. Starnes
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  2. Matthew D. McEvoy
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  3. Jesse M. Ehrenfeld
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  4. Warren S. Sandberg
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  5. Jonathan P. Wanderer
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Corresponding author

Correspondence to Joseph R. Starnes.

Additional information

This article is part of the Topical Collection on Education and Training

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Starnes, J.R., McEvoy, M.D., Ehrenfeld, J.M. et al. Automated Case Cancellation Review System Improves Systems-Based Practice. J Med Syst 39, 134 (2015). https://doi.org/10.1007/s10916-015-0330-3

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  • DOI: https://doi.org/10.1007/s10916-015-0330-3

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