An objective approach to evaluate novice robotic surgeons using a combination of kinematics and stepwise cumulative sum (CUSUM) analyses.

BACKGROUND: Current evaluation methods for robotic-assisted surgery (ARCS or GEARS) are limited to 5-point Likert scales which are inherently time-consuming and require a degree of subjective scoring. In this study, we demonstrate a method to break down complex robotic surgical procedures using a combination of an objective cumulative sum (CUSUM) analysis and kinematics data obtained from the da Vinci® Surgical System to evaluate the performance of novice robotic surgeons. METHODS: Two HPB fellows performed 40 robotic-assisted hepaticojejunostomy reconstructions to model a portion of a Whipple procedure. Kinematics data from the da Vinci® system was recorded using the dV Logger® while CUSUM analyses were performed for each procedural step. Each kinematic variable was modeled using machine learning to reflect the fellows' learning curves for each task. Statistically significant kinematics variables were then combined into a single formula to create the operative robotic index (ORI). RESULTS: The inflection points of our overall CUSUM analysis showed improvement in technical performance beginning at trial 16. The derived ORI model showed a strong fit to our observed kinematics data (R2 = 0.796) with an ability to distinguish between novice and intermediate robotic performance with 89.3% overall accuracy. CONCLUSIONS: In this study, we demonstrate a novel approach to objectively break down novice performance on the da Vinci® Surgical System. We identified kinematics variables associated with improved overall technical performance to create an objective ORI. This approach to robotic operative evaluation demonstrates a valuable method to break down complex surgical procedures in an objective, stepwise fashion. Continued research into objective methods of evaluation for robotic surgery will be invaluable for future training and clinical implementation of the robotic platform.

Impact of Multidisciplinary Audit of Enhanced Recovery After Surgery (ERAS)® Programs at a Single Institution.

BACKGROUND: As Enhanced Recovery After Surgery (ERAS®) programs expand across numerous subspecialties, growth and sustainability on a system level becomes increasingly important and may benefit from reporting multidisciplinary and financial data. However, the literature on multidisciplinary outcome analysis in ERAS is sparse. This study aims to demonstrate the impact of multidisciplinary ERAS auditing in a hospital system. Additionally, we describe developing a financial metric for use in gaining support for system-wide ERAS adoption and sustainability. METHODS: Data from HPB, colorectal and urology ERAS programs at a single institution were analyzed from a prospective ERAS Interactive Audit System (EIAS) database from September 2015 to June 2019. Clinical 30-day outcomes for the ERAS cohort (n = 1374) were compared to the EIAS pre-ERAS control (n = 311). Association between improved ERAS compliance and improved outcomes were also assessed for the ERAS cohort. The potential multidisciplinary financial impact was estimated from hospital bed charges. RESULTS: Multidisciplinary auditing demonstrated a significant reduction in postoperative length of stay (LOS) (1.5 days, p < 0.001) for ERAS patients in aggregate and improved ERAS compliance was associated with reduced LOS (coefficient - 0.04, p = 0.004). Improved ERAS compliance in aggregate also significantly associated with improved 30-day survival (odds ratio 1.04, p = 0.001). Multidisciplinary analysis also demonstrated a potential financial impact of 44% savings (p < 0.001) by reducing hospital bed charges across all specialties. CONCLUSIONS: Multidisciplinary auditing of ERAS programs may improve ERAS program support and expansion. Analysis across subspecialties demonstrated associations between improved ERAS compliance and postoperative LOS as well as 30-day survival, and further suggested a substantial combined financial impact.

The next step in surgical quality improvement: outcome situational awareness

Summary: A similar theme unites proposed solutions for stagnant improvement in outcomes and rising health care costs: eliminate unnecessary variation in the care of surgical patients. While large quality-improvement projects like the Americal College of Surgeons National Surgical Quality Improvement Program have historically led to improved patient outcomes at the hospital level, the next step in surgical quality improvement is to eliminate unnecessary variation at the level of the individual surgeon. Critical examination of individualized clinical, financial and patient-reported outcomes ­ outcome situational awareness ­ along with peer group comparison will help surgeons to identify variation in patient care. We are piloting an interactive software platform at our institution to provide information on individualized clinical, financial and patient-reported outcomes in real time through automatic data population of a central REDCap database. These individualized data along with peer group comparison allow surgeons to objectively determine areas of potential improvement.

Experimental High-Frequency Irreversible Electroporation Using a Single-Needle Delivery Approach for Nonthermal Pancreatic Ablation In Vivo.

PURPOSE: To investigate the feasibility of single-needle high-frequency irreversible electroporation (SN-HFIRE) to create reproducible tissue ablations in an in vivo pancreatic swine model. MATERIALS AND METHODS: SN-HFIRE was performed in swine pancreas in vivo in the absence of intraoperative paralytics or cardiac synchronization using 3 different voltage waveforms (1-5-1, 2-5-2, and 5-5-5 [on-off-on times (µs)], n = 6/setting) with a total energized time of 100 µs per burst. At necropsy, ablation size/shape was determined. Immunohistochemistry was performed to quantify apoptosis using an anticleaved caspase-3 antibody. A numerical model was developed to determine lethal thresholds for each waveform in pancreas. RESULTS: Mean tissue ablation time was 5.0 ± 0.2 minutes, and no cardiac abnormalities or muscle twitch was detected. Mean ablation area significantly increased with increasing pulse width (41.0 ± 5.1 mm2 [range 32-66 mm2] vs 44 ± 2.1 mm2 [range 38-56 mm2] vs 85.0 ± 7.0 mm2 [range 63-155 mm2]; 1-5-1, 2-5-2, 5-5-5, respectively; p < 0.0002 5-5-5 vs 1-5-1 and 2-5-2). The majority of the ablation zone did not stain positive for cleaved caspase-3 (6.1 ± 2.8% [range 1.8-9.1%], 8.8 ± 1.3% [range 5.5-14.0%], and 11.0 ± 1.4% [range 7.1-14.2%] cleaved caspase-3 positive 1-5-1, 2-5-2, 5-5-5, respectively), with significantly more positive staining at the 5-5-5 pulse setting compared with 1-5-1 (p < 0.03). Numerical modeling determined a lethal threshold of 1114 ± 123 V/cm (1-5-1 waveform), 1039 ± 103 V/cm (2-5-2 waveform), and 693 ± 81 V/cm (5-5-5 waveform). CONCLUSIONS: SN-HFIRE induces rapid, predictable ablations in pancreatic tissue in vivo without the need for intraoperative paralytics or cardiac synchronization.

Robotic-assisted versus laparoscopic left pancreatectomy at a high-volume, minimally invasive center.

INTRODUCTION: While minimally invasive left pancreatectomy has become more widespread and generally accepted over the last decade, opinions on modality of minimally invasive approach (robotic or laparoscopic) remain mixed with few institutions performing a significant portion of both operative approaches simultaneously. METHODS: 247 minimally invasive left pancreatectomies were retrospectively identified in a prospectively maintained institutional REDCap™ database, 135 laparoscopic left pancreatectomy (LLP) and 108 robotic-assisted left pancreatectomy (RLP). Demographics, intraoperative variables, postoperative outcomes, and OR costs were compared between LLP and RLP with an additional subgroup analysis for procedures performed specifically for pancreatic adenocarcinoma (35 LLP and 23 RLP) focusing on pathologic outcomes and 2-year actuarial survival. RESULTS: There were no significant differences in preoperative demographics or indications between LLP and RLP with 34% performed for chronic pancreatitis and 23% performed for pancreatic adenocarcinoma. While laparoscopic cases were faster (p < 0.001) robotic cases had a higher rate of splenic preservation (p < 0.001). Median length of stay was 5 days for RLP and LLP, and rate of clinically significant grade B/C pancreatic fistula was approximately 20% for both groups. Conversion rates to laparotomy were 4.3% and 1.8% for LLP and RLP approaches respectively. RLP had a higher rate of readmission (p = 0.035). Pathologic outcomes and 2-year actuarial survival were similar between LLP and RLP. LLP on average saved $206.67 in OR costs over RLP. CONCLUSIONS: This study demonstrates that at a high-volume center with significant minimally invasive experience, both LLP and RLP can be equally effective when used at the discretion of the operating surgeon. We view the laparoscopic and robotic platforms as tools for the modern surgeon, and at our institution, given the technical success of both operative approaches, we will continue to encourage our surgeons to approach a difficult operation with their tool of choice.

Use of Artificial Intelligence Deep Learning to Determine the Malignant Potential of Pancreatic Cystic Neoplasms With Preoperative Computed Tomography Imaging.

BACKGROUND: Society consensus guidelines are commonly used to guide management of pancreatic cystic neoplasms (PCNs). However, downsides of these guidelines include unnecessary surgery and missed malignancy. The aim of this study was to use computed tomography (CT)-guided deep learning techniques to predict malignancy of PCNs. MATERIALS AND METHODS: Patients with PCNs who underwent resection were retrospectively reviewed. Axial images of the mucinous cystic neoplasms were collected and based on final pathology were assigned a binary outcome of advanced neoplasia or benign. Advanced neoplasia was defined as adenocarcinoma or intraductal papillary mucinous neoplasm with high-grade dysplasia. A convolutional neural network (CNN) deep learning model was trained on 66% of images, and this trained model was used to test 33% of images. Predictions from the deep learning model were compared to Fukuoka guidelines. RESULTS: Twenty-seven patients met the inclusion criteria, with 18 used for training and 9 for model testing. The trained deep learning model correctly predicted 3 of 3 malignant lesions and 5 of 6 benign lesions. Fukuoka guidelines correctly classified 2 of 3 malignant lesions as high risk and 4 of 6 benign lesions as worrisome. Following deep learning model predictions would have avoided 1 missed malignancy and 1 unnecessary operation. DISCUSSION: In this pilot study, a deep learning model correctly classified 8 of 9 PCNs and performed better than consensus guidelines. Deep learning can be used to predict malignancy of PCNs; however, further model improvements are necessary before clinical use.

Robotic-assisted completion cholecystectomy: A safe and effective approach to a challenging surgical scenario - A single center retrospective cohort study.

BACKGROUND: Reoperation following a previous subtotal or aborted cholecystectomy presents a challenging surgical scenario that has traditionally required an open completion cholecystectomy. The aim of this study was to describe an institutional experience with a robotic-assisted approach to completion cholecystectomy. METHODS: A database was retrospectively audited to identify all patients who underwent robotic-assisted cholecystectomy performed by two hepatopancreatobiliary surgeons at a single centre from 2010 to 2019. RESULTS: Twenty six patients who underwent a robotic-assisted completion cholecystectomy were identified. Median operative time was 142 min (48-247 min) with a blood loss of 50 cc (0-500 cc). Minor complications (Clavien-Dindo ≤ II 90 days) occurred in three patients (11.5%) with no major complication or mortality reported. Median hospital length of stay was 1 day (0-6 days) with one patient readmitted. CONCLUSION: This study represents to our knowledge the largest series of robotic-assisted completion cholecystectomies to date. The robotic approach appears to be a safe and effective procedure associated with a low morbidity and high success rate.

A Single-Center Experience with Minimally Invasive Transgastric ERCP in Patients with Previous Gastric Bypass: Lessons Learned and Technical Considerations.

As bariatric surgery increases, there is a growing population of patients with biliary obstruction and anatomy which precludes transoral access through endoscopic retrograde cholangiopancreatography (ERCP). Minimally invasive transgastric ERCP (TG-ERCP) offers a feasible alternative for the treatment. A retrospective review was performed of all patients who underwent laparoscopic or robotic-assisted TG-ERCP between 2010 and 2017. Chart abstraction collected demographics, procedural details, success rate, and postoperative outcomes. Forty patients were identified, of which 38 cases were performed laparoscopically and two robotically. Median operative time was 163 minutes, with an estimated blood loss of 50 cc. TG-ERCP was performed successfully in 36 cases (90%); sphincterotomy was completed in 35 patients (97%). Sixty per cent already had a cholecystectomy; in the remaining patients, it was performed concurrently. Major complications included stomach perforation (n = 1), pancreatitis (n = 3), and anemia requiring transfusion (n = 2). In patients with biliary obstruction and anatomy not suitable for ERCP, TG-ERCP can be performed in a minimally invasive fashion, with a high rate of technical success and low morbidity. We describe a stepwise, reproducible technique because it is an essential tool for the shared armamentarium of endoscopists and surgeons.

Modifying Interhospital Hepatopancreatobiliary Transfers Based on Predictive Analytics: Moving from a Center of Excellence to a Health-Care System of Excellence.

Regionalization of complex surgical care has increased interhospital transfers to quaternary centers within large health-care systems. Risk-based patient selection is imperative to improve resource allocation without compromising care. This study aimed to develop predictive models for identifying low-risk patients for transfer to a fully integrated satellite hepatopancreatobiliary (HPB) service in the northeast region of the health-care system. HPB transfers to the quaternary center over 15 months from hospitals in proximity to the satellite HPB center. A predictive tool was developed based on simple pretransfer variables and outcomes for 30-day major complications (Clavien grade ≥ 3), readmission, and mortality. Thresholds for "low risk" were set at different SDs below mean for each model. Predictive models were developed from 51 eligible northeast region patient transfers for major complications (Brier score 0.1948, receiver operator characteristic (ROC) 0.7123, P = 0.0009), readmission (Brier score 0.0615, ROC 0.7368, P = 0.0020), and mortality (Brier score 0.0943, ROC 0.7989, P = 0.0023). Thresholds set from 2 SD below the mean for all models identified 2 as "low risk." Adjusting the threshold for the serious complication model to only 1 SD below the mean increased the "low-risk" cohort to five patients. These models demonstrate an easy-to-use tool to assist surgeons in identifying low-risk patients for diversion to a fully integrated satellite center. Improved interhospital transfers within a region could begin a transition from centers of excellence toward health-care systems of excellence.

Clinically Meaningful Laboratory Protocols Reduce Hospital Charges Based on Institutional and ACS-NSQIP® Risk Calculators in Hepatopancreatobiliary Surgery.

Postoperative laboratory testing is an underrecognized but substantial contributor to health-care costs. We aimed to develop and validate a clinically meaningful laboratory (CML) protocol with individual risk stratification using generalizable and institution-specific predictive analytics to reduce laboratory testing and maximize cost savings for low-risk patients. An institutionally based risk model was developed for pancreaticoduodenectomy and hepatectomy, and an ACS-NSQIP®-based model was developed for distal pancreatectomy. Patients were stratified in each model to the CML by individual risk of major complications, readmission, or death. Clinical outcomes and estimated cost savings were compared with those of a historical cohort with standard of care. Over 34 months, 394 patients stratified to the CML for pancreaticoduodenectomy or hepatectomy saved an estimated $803,391 (44.4%). Over 13 months, 52 patients stratified to the CML for distal pancreatectomy saved an estimated $81,259 (30.5%). Clinical outcomes for 30-day major complications, readmission, and mortality were unchanged after implementation of either model. Predictive analytics can target low-risk patients to reduce laboratory testing and improve cost savings, regardless of whether an institutional or a generalized risk model is implemented. Broader application is important in patient-centered health care and should transition from predictive to prescriptive analytics to guide individual care in real time.

Current State of Enhanced Recovery After Surgery in Hepatopancreatobiliary Surgery.

For over two decades, enhanced recovery pathways have been implemented in many surgical disciplines, most notably in colorectal surgery. Since 2001, the Enhanced Recovery After Surgery (ERAS®) Study Group has developed a main protocol comprising 24 evidence-based core items. While these core items unite similar preoperative, intraoperative, and postoperative principles across surgical subspecialties, variations and modifications exist to these core items based on unique considerations for each surgical subspecialty. This overview will summarize overarching principles for ERAS within hepatopancreaticobiliary (HPB) surgery, first summarizing Pancreaticoduodenectomy and Hepatectomy ERAS Society Guidelines. Specifically, principles and areas of current debate regarding preoperative oral carbohydrate loading/fasting, perioperative fluid management, and analgesia will be discussed. While institutions are beginning to realize both clinical and financial benefits of ERAS within HPB surgery, enhanced recovery remains a relatively recent phenomenon within the field. The complex patient population, high morbidity, and resource-intensive care involved in HPB surgery certainly warrant special consideration. To continue to promote improved clinical outcomes in a cost-effective manner, the ERAS Society will continue to actively address concerns and ensure all recommendations are based on the most up-to-date scientific evidence within the field of HPB surgery.

Discrepancy in Postoperative Outcomes between Auditing Databases: A NSQIP Comparison.

In 2014, ACS-NSQIP® targeted pancreatectomies to improve outcome reporting and risk calculation related to pancreatectomy. At the same time, our department began prospectively collecting data for pancreatectomy in the Enhanced Recovery After Surgery® Interactive Audit System (EIAS). The purpose of this study is to compare reported outcomes between two major auditing databases for the same patients undergoing pancreatectomy. The same 171 patients were identified in both databases. Clinical outcomes were then obtained from each database and compared to determine whether reported complication rates were statistically different between auditing databases. A combination of Wilcoxon rank sum and Pearson's chi-squared tests were used to calculate statistical significance. No significant difference was appreciated in captured demographics between EIAS and NSQIP. Significant differences in reported rates for renal dysfunction, postoperative pancreatic fistula, return to the operative room, and urinary tract infection were noted between EIAS and NSQIP. Although significant differences in reported complication rates were demonstrated between EIAS and NSQIP for pancreatectomy, much of the discrepancy is attributable to subtle differences in definitions for postoperative occurrences between the two auditing databases. It is vital for surgeons to understand the exact definition that determines the complication rate for a given database.