The impact of days off between cases on perioperative outcomes for robotic-assisted laparoscopic prostatectomy

Gamification of robotic simulation to train general surgery residents

BACKGROUND

Gamification applies game design elements to non-game contexts in order to engage participation and increase learner motivation. Robotic surgery is gaining popularity in general surgery but requires specialized technical skills. We sought to determine whether gamification of robotic simulation training could increase robotic simulator utilization among general surgery residents.

METHODS

General surgery residents were recruited and sent weekly progress on simulator performance including leaderboards for 4 weeks during the intervention periods. There were also two control periods setup in an ABAB study design. Usage time and mean scores were compared between the control periods and intervention periods. A post-study qualitative assessment interview using semi-structured interviews determined barriers and motivational components of simulator usage.

RESULTS

Fifteen general surgery residents enrolled in the study (n = 15). Intervention increased total simulator usage time 9.7-fold from 153 to 1485 min. Total simulator days increased threefold from 9 to 27 days. Resident participation increased from 33 to 53%. Median average scores were higher during the intervention periods (58.8 and 81.9 vs 44.0). During the first intervention period, median individual-level simulator usage time increased 17 min (P = 0.03). However, there was no individual-level increase in median usage minutes or days during the second intervention period. Qualitative assessment determined barriers to be limited time due to clinical duties, and simulator availability while motivational factors included competitive factors such as leaderboards and gaming aspects. Potential improvements were increasing attending visibility of scores to increase recognition of progress by the residents and creating dedicated time for training.

CONCLUSION

Gamification of robotic simulation training increased general surgery resident participation, usage time and scores. Impact was not durable. Instituting dedicated practice time and more attending engagement may increase trainee motivation and performance.

The association between labour epidural case volume and the rate of accidental dural puncture

Accidental dural puncture is a recognised complication of labour epidural placement and can cause a debilitating headache. We examined the association between labour epidural case volume and accidental dural puncture rate in specialist anaesthetists and anaesthesia trainees. We performed a retrospective cohort study of labour epidural and combined spinal-epidural nerve blocks performed between 1 July 2013 and 31 December 2017 at Waitemata District Health Board, Auckland, New Zealand. The mean (SD) annual number of obstetric epidural and combined spinal-epidural procedures for high-case volume specialists was 44.2 (15.0), and for low-case volume specialists was 10.0 (6.8), after accounting for caesarean section combined spinal-epidural procedures. Analysis of 7976 labour epidural and combined spinal-epidural procedure records revealed a total of 92 accidental dural punctures (1.2%). The accidental dural puncture rate (95%CI) in high-case volume specialists was 0.6% (0.4-0.9%) and in low-case volume specialists 2.4% (1.4-3.9%), indicating probable skill decay. The odds of accidental dural puncture were 3.77 times higher for low- compared with high-case volume specialists (95%CI 1.72-8.28, p = 0.001). Amongst trainees, novices had a significantly higher accidental dural puncture complication rate (3.1%) compared with registrars (1.2%), OR (95%CI) 0.39 (0.18-0.84), p = 0.016, or fellows (1.1%), 0.35 (0.16-0.76), p = 0.008. Accidental dural puncture complication rates decreased once trainees progressed past the 'novice' training stage.

Advantages of, and Adaptations to, Enhanced Recovery Protocols for Perioperative Care during the COVID-19 Pandemic

Objective

This review formulates the rationale for using enhanced recovery protocols (ERPs) to standardize and optimize perioperative care during this high-risk time to minimize poor outcomes owing to provider, patient, and system vulnerabilities.

Data Sources

n/a

Methods of Study Selection

A literature review using key Medical Subject Headings terms was performed—according to methods described by the Cochrane Collaboration and Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidelines—on studies that described enhanced recovery and coronavirus disease (COVID-19).

Tabulation, Integration, and Results

Modifications to our existing ERPs related to the COVID-19 pandemic should include new accommodations for patient education, preoperative COVID-19 testing, prehabilitation, and intraoperative infection as well as thromboembolism risk reduction.

Conclusion

ERPs are evidence-based, best practice guidelines applied across the perioperative continuum to mitigate surgical stress, decrease complications, and accelerate recovery. These benefits are part of the high-value–care equation needed to solve the clinical, operational, and financial challenges of the current COVID-19 pandemic. The factors driving outcomes on ERPs, such as the provision of minimally invasive surgery, warrant careful consideration. Tracking patient outcomes and improving care in response to outcomes data are key to the success of clinical care protocols such as ERPs. Numerous emerging clinical registries and reporting systems have been activated to provide outcomes data on the impact of COVID-19. This will inform and change surgical practice as well as provide opportunity to learn if the advantages that surgeons, patients, and the healthcare system might gain from using ERPs during a pandemic are meaningful.

How to Bring Surgery to the Next Level: Interpretable Skills Assessment in Robotic-Assisted Surgery

Introduction

A surgeon's technical skills are an important factor in delivering optimal patient care. Most existing methods to estimate technical skills remain subjective and resource intensive. Robotic-assisted surgery (RAS) provides a unique opportunity to develop objective metrics using key elements of intraoperative surgeon behavior which can be captured unobtrusively, such as instrument positions and button presses. Recent studies have shown that objective metrics based on these data (referred to as objective performance indicators [OPIs]) correlate to select clinical outcomes during robotic-assisted radical prostatectomy. However, the current OPIs remain difficult to interpret directly and, therefore, to use within structured feedback to improve surgical efficiencies.

Methods

We analyzed kinematic and event data from da Vinci surgical systems (Intuitive Surgical, Inc., Sunnyvale, CA, USA) to calculate values that can summarize the use of robotic instruments, referred to as OPIs. These indicators were mapped to broader technical skill categories of established training protocols. A data-driven approach was then applied to further sub-select OPIs that distinguish skill for each technical skill category within each training task. This subset of OPIs was used to build a set of logistic regression classifiers that predict the probability of expertise in that skill to identify targeted improvement and practice. The final, proposed feedback using OPIs was based on the coefficients of the logistic regression model to highlight specific actions that can be taken to improve.

Results

We determine that for the majority of skills, only a small subset of OPIs (2-10) are required to achieve the highest model accuracies (80-95%) for estimating technical skills within clinical-like tasks on a porcine model. The majority of the skill models have similar accuracy as models predicting overall expertise for a task (80-98%). Skill models can divide a prediction into interpretable categories for simpler, targeted feedback.

Conclusion

We define and validate a methodology to create interpretable metrics for key technical skills during clinical-like tasks when performing RAS. Using this framework for evaluating technical skills, we believe that surgical trainees can better understand both what can be improved and how to improve.

Evidence that surgical performance predicts clinical outcomes

PURPOSE

Assessment of surgeon performance in the operating room has been identified as a direct method of measuring surgical quality. Studies published in urology and other surgical disciplines have investigated this link directly by measuring surgeon and team performance using methodology supported by validity evidence. This article highlights the key findings of these studies and associated underlying concepts.

METHODS

​Seminal literature from urology and related areas of research was used to inform this review of the performance-outcome relationship in surgery. Current efforts to further our understanding of this concept are discussed, including relevant quality improvement and educational interventions that utilize this relationship.

RESULTS

Evidence from multiple surgical specialties and procedures has established the association between surgeon skill and clinically significant patient outcomes. Novel methods of measuring performance utilize surgeon kinematics and artificial intelligence techniques to more reliably and objectively quantify surgical performance.

CONCLUSIONS

Future directions include the use of this data to create interventions for quality improvement, as well as innovate the credentialing and recertification process for practicing surgeons.

Positive surgical margin rates during the robot-assisted laparoscopic radical prostatectomy learning curve of an experienced laparoscopic surgeon

INTRODUCTION

Since its introduction, robot-assisted laparoscopic radical prostatectomy (RARP) has gained widespread popularity, but is associated with a variable learning curve. Herein, we report the positive surgical margin (PSM) rates during the RARP learning curve of a single surgeon with significant previous laparoscopic radical prostatectomy (LRP) experience.

METHODS

We performed a prospective cohort study of the first 400 men with prostate cancer treated with RARP by a single surgeon (BS) with significant LRP experience. Our primary outcome was the impact of case timing in the learning curve on margin status. Our analysis was conducted by dividing the case numbers into quartiles (Q1-Q4) and determining if a case falling into an earlier quartile had an impact on margin status relative to the most recent quartile (Q4).

RESULTS

The Q1 cases had an odds ratio for margin positivity of 1.74 compared to Q4 (p=0.1). Multivariate logistic regression did not demonstrate case number to be a significant predictor of PSM. The mean Q1 operative time was 207.4 minutes, decreasing to 179.2 by Q4 (p<0.0001). The mean Q1 estimated blood loss was 255.1 ml, decreasing to 213.6 by Q4 (p=0.0064). There was no change in length of hospitalization within the study period.

CONCLUSIONS

Even when controlling for copredictors, a statistically significant learning curve for PSM rate of a surgeon with significant previous LRP experience was not detected during the first 400 RARP cases. We hypothesize that previous LRP experience may reduce the RARP PSM learning curve.