A novel approach to quantifying surgical workflow in robotic-assisted lobectomy.

INTRODUCTION: Understanding surgical workflow is critical for optimizing efficiencies and outcomes; however, most research evaluating workflow is impacted by observer subjectivity, limiting its reproducibility, scalability, and actionability. To address this, we developed a novel approach to quantitatively describe workflow within robotic-assisted lobectomy (RL). We demonstrate the utility of this approach by analysing features of surgical workflow that correlate with procedure duration. METHODS: RL was deconstructed into 12 tasks by expert thoracic surgeons. Task start and stop times were annotated across videos of 10 upper RLs (5 right and 5 left). Markov Networks were used to estimate both the likelihood of transitioning from one task to another and each task-transition entropy (i.e. complexity). Associations between the frequency with which each task was revisited intraoperatively and procedure duration were assessed using Pearson's correlation coefficient. RESULTS: Entropy calculations identified fissure dissection and hilar node dissection as tasks with especially complex transitions, while mediastinal lymph node dissection and division of pulmonary veins were less complex. The number of transitions to three tasks significantly correlated with case duration (fissure dissection (R = 0.69, p = 0.01), dissect arteries (R = 0.59, p = 0.03), and divide arteries (R = 0.63, p = 0.03)). CONCLUSION: This pilot demonstrates the feasibility of objectively quantifying workflow between RL tasks and introduces entropy as a new metric of task-transition complexity. These innovative measures of surgical workflow enable detailed characterization of a given surgery and might indicate behaviour that impacts case progression. We discuss how these measures can serve as a foundation and be combined with relevant clinical information to better understand factors influencing surgical inefficiency.

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

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.

Decreased Leak Rate and Need for Reintervention with Use of Closed Suction Calibration System: a Bariatric Surgery Quality Improvement Project.

BACKGROUND: Laparoscopic sleeve gastrectomy (SG) continues to grow in popularity as a primary bariatric procedure. The purpose of this study is to determine if leak rates and need for subsequent interventions are changed by the standardized use of a closed suction calibration system (CSCS) at a high-volume urban hospital. METHODS: A retrospective review was conducted between January 1, 2016, and December 31, 2018, on SG patients. All cases performed in 2018 were completed with a closed suction calibration system. Patient demographics, comorbidities, operative variables, and outcomes were collected. Descriptive statistics and chi-squared test were used to compare the two groups. Logistic regression models were adjusted for patient- and procedure-specific factors. RESULTS: Four hundred ninety cases were performed before and 195 after institution of the CSCS. Groups were similar in most characteristics, including median body mass index (BMI) (46.4 vs 45.8 kg/m2, p = 0.79). Those in the closed suction cohort were more likely to have OSA requiring therapy (32.4% vs 46.6%, p < 0.01) and to have their cases performed robotically (55.4% vs 39.6%, p = 0.02). Post introduction of the CSCS, the overall leak rate was 0% (1.4% vs 0%, p = 0.09); overall need for postoperative interventions decreased (9.6% vs 2.6%, p = 0.009). After adjustment, a 69% decrease was observed in need for related additional intervention [aOR 0.31 (0.12-0.81), p = 0.017]. CONCLUSION: The use of a standardized closed suction calibration system resulted in overall decreased leak rates, which was associated with a clinically significant decrease in additional interventions.

How We Do It: Implementing a Virtual, Multi-Institutional Collaborative Education Model for the COVID-19 Pandemic and Beyond.

OBJECTIVE: To describe the implementation of a virtual, multi-institutional educational collaboration involving over 50 general surgery residency programs during the COVID-19 pandemic that enabled enhanced learning for surgical residents despite social-distancing requirements. DESIGN: Description of Virginia Commonwealth University's virtual educational augmentation program and the development of a collaborative teaching network during the coronavirus pandemic. SETTING: This collaboration was initiated by Virginia Commonwealth University's Department of Surgery, Richmond, VA, and grew to include general surgery residency programs from across the nation. PARTICIPANTS: General surgery residents and faculty from Departments of General Surgery were recruited locally via direct emails and nationally via the Association of Program Directors' listserv and Twitter. In total, 52 institutions participated from every part of the country. RESULTS: A virtual, multi-institutional collaborative lecture series was initiated that grew to involve over 50 general surgery residency programs, allowing for daily didactics by experts in their fields during the initial surge of the COVID-19 pandemic, while maintaining social distancing and the provision of essential clinical care. CONCLUSION: A multi-institutional collaboration enabled continued didactic education during the coronavirus pandemic, vastly broadening the expertise, scope and variety available to residents, while decreasing burden on faculty. We believe this can serve as a framework for future multi-institutional collaborations that extend beyond the COVID-19 era.