Development of a Model for Video-Assisted Postoperative Team Debriefing.

J Surg Res

Department of Surgery, Amsterdam Gastroenterology and Metabolism, Amsterdam UMC, University of Amsterdam, Amsterdam, the Netherlands; Division of Surgery, Li Ka Shing Knowledge Institute, St. Michaels Hospital, Toronto, Canada. Electronic address:

Published: January 2021

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Article Abstract

Background: Video-assisted debriefing may be a powerful tool to improve surgical team performance. Nevertheless, a true operating team debriefing culture is lacking to date. This study aimed to find evidence on how to debrief the surgical team and develop a model suitable for debriefing using a video and medical data recorder (MDR) in the operating room (OR).

Methods: A review of the PubMed and Embase databases and Cochrane Library was performed. The identified literature was studied and combined with a conceptual framework to develop a model for postoperative video-assisted team debriefing. Thirty-five surgical cases were recorded with an MDR and debriefed with the operating team using the proposed debrief model and a standardized video-assisted performance report. A questionnaire was used to assess the participants' satisfaction with this debrief model.

Results: Debrief models and methods are extensively described in the current medical literature. An overview was provided. The OR team needs a structured debrief model, minimizing resource, effort, and motivational constraints. A structured six-step team debrief model suitable for video-assisted OR team debriefing was developed. The model was tested in 35 multidisciplinary MDR-assisted debriefing sessions and the debriefing sessions were overall rated with a mean of 7.8 (standard deviation 1.4, 10-point Likert scale) by participants.

Conclusions: Debriefing surgical teams using a video and MDR in the OR requires a model on how to use such recordings optimally. To date, no such model existed. The proposed debrief model was tested using a multisource MDR and may be used to facilitate OR debriefing across various settings.

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http://dx.doi.org/10.1016/j.jss.2020.07.065DOI Listing

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