Literature DB >> 25761143

Assessment of quality outcomes for robotic pancreaticoduodenectomy: identification of the learning curve.

Brian A Boone1, Mazen Zenati1, Melissa E Hogg1, Jennifer Steve1, Arthur James Moser2, David L Bartlett1, Herbert J Zeh1, Amer H Zureikat1.   

Abstract

IMPORTANCE: Quality assessment is an important instrument to ensure optimal surgical outcomes, particularly during the adoption of new surgical technology. The use of the robotic platform for complex pancreatic resections, such as the pancreaticoduodenectomy, requires close monitoring of outcomes during its implementation phase to ensure patient safety is maintained and the learning curve identified.
OBJECTIVE: To report the results of a quality analysis and learning curve during the implementation of robotic pancreaticoduodenectomy (RPD). DESIGN, SETTING, AND PARTICIPANTS: A retrospective review of a prospectively maintained database of 200 consecutive patients who underwent RPD in a large academic center from October 3, 2008, through March 1, 2014, was evaluated for important metrics of quality. Patients were analyzed in groups of 20 to minimize demographic differences and optimize the ability to detect statistically meaningful changes in performance. EXPOSURES: Robotic pancreaticoduodenectomy. MAIN OUTCOMES AND MEASURES: Optimization of perioperative outcome parameters.
RESULTS: No statistical differences in mortality rates or major morbidity were noted during the study. Statistical improvements in estimated blood loss and conversions to open surgery occurred after 20 cases (600 mL vs 250 mL [P = .002] and 35.0% vs 3.3% [P < .001], respectively), incidence of pancreatic fistula after 40 cases (27.5% vs 14.4%; P = .04), and operative time after 80 cases (581 minutes vs 417 minutes [P < .001]). Complication rates, lengths of stay, and readmission rates showed continuous improvement that did not reach statistical significance. Outcomes for the last 120 cases (representing optimized metrics beyond the learning curve) included a mean operative time of 417 minutes, median estimated blood loss of 250 mL, a conversion rate of 3.3%, 90-day mortality of 3.3%, a clinically significant (grade B/C) pancreatic fistula rate of 6.9%, and a median length of stay of 9 days. CONCLUSIONS AND RELEVANCE: Continuous assessment of quality metrics allows for safe implementation of RPD. We identified several inflexion points corresponding to optimization of performance metrics for RPD that can be used as benchmarks for surgeons who are adopting this technology.

Entities:  

Mesh:

Year:  2015        PMID: 25761143     DOI: 10.1001/jamasurg.2015.17

Source DB:  PubMed          Journal:  JAMA Surg        ISSN: 2168-6254            Impact factor:   14.766


  80 in total

Review 1.  Laparoscopic pancreatic surgery for benign and malignant disease.

Authors:  Thijs de Rooij; Sjors Klompmaker; Mohammad Abu Hilal; Michael L Kendrick; Olivier R Busch; Marc G Besselink
Journal:  Nat Rev Gastroenterol Hepatol       Date:  2016-02-17       Impact factor: 46.802

2.  Can post-hoc video review of robotic pancreaticoduodenectomy predict portal/superior mesenteric vein margin status in pancreatic adenocarcinoma?

Authors:  Jae P Jung; Mazen S Zenati; Ahmad Hamad; Melissa E Hogg; Richard L Simmons; Amer H Zureikat; Herbert J Zeh; Brian A Boone
Journal:  HPB (Oxford)       Date:  2018-11-28       Impact factor: 3.647

Review 3.  Surgical resection of pancreatic neuroendocrine neoplasm by minimally invasive surgery-the robotic approach?

Authors:  Roxanne Y A Teo; Brian K P Goh
Journal:  Gland Surg       Date:  2018-02

4.  [Laparoscopic pancreatoduodenectomy: risk without benefits?]

Authors:  O Strobel; M W Büchler
Journal:  Chirurg       Date:  2019-06       Impact factor: 0.955

5.  How I Do It: Robotic Pancreaticoduodenectomy.

Authors:  Sushruta S Nagarkatti; Amit V Sastry; Dionisios Vrochides; John B Martinie
Journal:  J Gastrointest Surg       Date:  2019-05-31       Impact factor: 3.452

Review 6.  Robotic gastrointestinal surgery: learning curve, educational programs and outcomes.

Authors:  Charles C Vining; Kinga B Skowron; Melissa E Hogg
Journal:  Updates Surg       Date:  2021-01-23

7.  Analysis of the Cost Effectiveness of Laparoscopic Pancreatoduodenectomy.

Authors:  Michael H Gerber; Daniel Delitto; Cristina J Crippen; Thomas J George; Kevin E Behrns; Jose G Trevino; Jessica L Cioffi; Steven J Hughes
Journal:  J Gastrointest Surg       Date:  2017-05-31       Impact factor: 3.452

8.  Determining the Adequate Examined Lymph Node Count in Resected Ampullary Adenocarcinoma-A National Cohort Study.

Authors:  Ibrahim Nassour; Alana Christie; Michael A Choti; John C Mansour; Rebecca M Minter; Patricio M Polanco; Mathew M Augustine; Matthew R Porembka; Xian-Jin Xie; Sam C Wang
Journal:  J Gastrointest Surg       Date:  2018-03-15       Impact factor: 3.452

Review 9.  What is the Learning Curve for Laparoscopic Major Hepatectomy?

Authors:  Kimberly M Brown; David A Geller
Journal:  J Gastrointest Surg       Date:  2016-03-08       Impact factor: 3.452

10.  Perioperative Outcomes of Robotic Pancreaticoduodenectomy: a Propensity-Matched Analysis to Open and Laparoscopic Pancreaticoduodenectomy.

Authors:  A Floortje van Oosten; Ding Ding; Joseph R Habib; Ahmer Irfan; Ryan K Schmocker; Elisabetta Sereni; Benedict Kinny-Köster; Michael Wright; Vincent P Groot; I Quintus Molenaar; John L Cameron; Martin Makary; Richard A Burkhart; William R Burns; Christopher L Wolfgang; Jin He
Journal:  J Gastrointest Surg       Date:  2020-11-17       Impact factor: 3.452

View more

北京卡尤迪生物科技股份有限公司 © 2022-2023.