Objective performance indicators of cardiothoracic residents are associated with vascular injury during robotic-assisted lobectomy on porcine models

John F. Lazar, Kristen Brown, Sadia Yousaf, Anthony Jarc, Ariana Metchik, Hayley Henderson, Richard H. Feins, Manu S. Sancheti, Jules Lin, Stephen Yang, Jonathan Nesbitt, Desmond D’Souza, Daniel S. Oh

Research output: Contribution to journalArticlepeer-review

Abstract

Surgical training relies on subjective feedback on resident technical performance by attending surgeons. A novel data recorder connected to a robotic-assisted surgical platform captures synchronized kinematic and video data during an operation to calculate quantitative, objective performance indicators (OPIs). The aim of this study was to determine if OPIs during initial task of a resident’s robotic-assisted lobectomy (RL) correlated with bleeding during the procedure. Forty-six residents from the 2019 Thoracic Surgery Directors Association Resident Boot Camp completed RL on an ex vivo perfused porcine model while continuous video and kinematic data were recorded. For this pilot study, RL was segmented into 12 tasks and OPIs were calculated for the initial major task. Cases were reviewed for major bleeding events and OPIs of bleeding cases were compared to those who did not. Data from 42 residents were complete and included in the analysis. 10/42 residents (23.8%) encountered bleeding: 10/40 residents who started with superior pulmonary vein exposure and 0/2 residents who started with pulmonary artery exposure. Twenty OPIs for both hands were assessed during the initial task. Six OPIs related to instrument usage or smoothness of motion were significant for bleeding. Differences were statistically significant for both hands (p < 0.05). OPIs showing bimanual asymmetry indicated lower proficiency. This study demonstrates that kinematic and video analytics can establish a correlation between objective performance metrics and bleeding events in an ex vivo perfused lobectomy. Further study could assist in the development of focused exercises and simulation on objective domains to help improve overall performance and reducing complications during RL.

Original languageEnglish (US)
Pages (from-to)669-676
Number of pages8
JournalJournal of Robotic Surgery
Volume17
Issue number2
DOIs
StatePublished - Apr 2023

Keywords

  • Innovation
  • Robotic surgery
  • Simulation
  • Surgical data science
  • Surgical education
  • Technical assessment

ASJC Scopus subject areas

  • Health Informatics
  • Surgery

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