The impact of hybrid coronary revascularization on hospital costs and reimbursements.

BACKGROUND: Hybrid coronary revascularization (HCR) combines a minimally invasive, left internal mammary artery-left anterior descending coronary artery (LAD) bypass with percutaneous intervention of non-LAD vessels for patients with multivessel coronary disease. The financial implications of HCR have not been compared with off-pump coronary artery bypass (OPCAB) through sternotomy. METHODS: The contribution margin is a fiduciary calculation (best hospital payment estimate--total variable costs) used by hospitals to determine fiscal viability of services. From 2010 to 2011, 26 Medicare patients underwent HCR at a single United States institution and were compared with 28 randomly selected, contemporaneous Medicare patients undergoing multivessel OPCAB. All HCR patients underwent a robotic-assisted, sternal-sparing, off-pump, left internal mammary artery-LAD anastomosis plus percutaneous intervention to non-LAD vessels. A linear regression model was used to compare fiscal and utilization outcomes of HCR to OPCAB adjusted for hospital length of stay and The Society of Thoracic Surgeons Predicted Risk of Mortality score. RESULTS: On regression analysis controlling for overall length of stay and Predicted Risk of Mortality score, the contribution margin (+$8,771, p<0.0001) was greater for HCR than for OPCAB. Despite higher total cost for HCR compared with OPCAB (+$7,026, p=0.001), the total variable cost (+$2,281, p=0.07) was not significantly different. Best payment estimates (+11,031, p<0.0001) and Medicare reimbursements (+$8,992, p=0.002) were higher for HCR than for OPCAB, and there was a reduction in blood transfusion (-1.5 units, p<0.0001), ventilator time (-10 hours, p=0.001), and postoperative length of stay (-1.2 days, p=0.002) for the HCR group. CONCLUSIONS: Compared with OPCAB, HCR results in a greater contribution margin for hospitals. This may result from higher reimbursement as well as improved resource utilization postoperatively, which may offset more expensive procedural costs associated with HCR.

Can we become better robot surgeons through simulator practice?

INTRODUCTION: There is significant growth in the use of the robotic surgery platform in the general surgery community. Current pre-requisites for robot surgery training include performing basic tasks on a simulator and achieving a minimum overall score for each task. However, there is limited information about these tasks related to performance and time required to become proficient. We focused on critical tasks that have the highest potential for preventing inadvertent injuries, and constructed models to predict how many attempts would be needed to master the tasks depending on the user's initial attempt. METHODS AND PROCEDURES: This study was conducted using de-identified data collected over 12 months from the dV-Trainers® simulator at our institution. We analyzed tasks used in institutional surgical robot credentialing that focused on camera manipulation and energy use. Data were extracted from the Camera Targeting, Energy Dissection, and Energy Switching exercises focusing on individual metrics such as Time to Complete Exercise, Economy of Motion, Misapplied Energy Time, and Blood Volume Loss. Mixed linear models looking at sequential attempts and specific performance metrics were constructed using IBM SPSS Statistics version 20. RESULTS: Over 26,000 overall minutes of recorded use was logged in our simulator by more than 30 unique users across all exercises. An average of 15 users performed each of the analyzed exercises, with an average of eight attempts per exercise. Based on our models, on average most users would need four to five attempts to achieve 80 % proficiency for any given metric. CONCLUSION: Virtual reality robotic simulators such as the dv-Trainer® can be used by general surgeons to become better robotic surgeons. Our data suggests that it can be used by a surgeon to predict how much time and effort one would need to spend on the simulator in order to become proficient with the robot, especially in critical metrics such as camera manipulation and energy application. Surgeons who require more attempts to successfully complete tasks may want to consider additional training methods, such as proctoring or hands-on laboratories, to improve robot surgery proficiency.