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

A challenge in reducing unwanted care variation is effectively managing the wide variety of performed surgical procedures. While an organization may perform thousands of types of cases, privacy and logistical constraints prevent review of previous cases to learn about prior practices. To bridge this...

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Bibliographic Details
Published in:Journal of clinical anesthesia 2021-02, Vol.68, p.110114-110114, Article 110114
Main Authors: Wanderer, Jonathan P., Lasko, Thomas A., Coco, Joseph R., Fowler, Leslie C., McEvoy, Matthew D., Feng, Xiaoke, Shotwell, Matthew S., Li, Gen, Gelfand, Brian J., Novak, Laurie L., Owens, David A., Fabbri, Daniel V.
Format: Article
Language:English
Subjects:
Academic Medical Centers
Anesthesia
Anesthesia - adverse effects
Anesthetic planning
Anesthetic training
Clinical Competence
Codes
Cross-Over Studies
Data models
Data visualization
Data warehouses
Humans
Internship and Residency
Medical practices
Statistical analysis
Usability
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Summary:A challenge in reducing unwanted care variation is effectively managing the wide variety of performed surgical procedures. While an organization may perform thousands of types of cases, privacy and logistical constraints prevent review of previous cases to learn about prior practices. To bridge this gap, we developed a system for extracting key data from anesthesia records. Our objective was to determine whether usage of the system would improve case planning performance for anesthesia residents. Randomized, cross-over trial. Vanderbilt University Medical Center. We developed a web-based, data visualization tool for reviewing de-identified anesthesia records. First year anesthesia residents were recruited and performed simulated case planning tasks (e.g., selecting an anesthetic type) across six case scenarios using a randomized, cross-over design after a baseline assessment. An algorithm scored case planning performance based on care components selected by residents occurring frequently among prior anesthetics, which was scored on a 0–4 point scale. Linear mixed effects regression quantified the tool effect on the average performance score, adjusting for potential confounders. We analyzed 516 survey questionnaires from 19 residents. The mean performance score was 2.55 ± SD 0.32. Utilization of the tool was associated with an average score improvement of 0.120 points (95% CI 0.060 to 0.179; p 
ISSN:0952-8180
1873-4529
DOI:10.1016/j.jclinane.2020.110114