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      Learning curve for robotic-assisted laparoscopic colorectal surgery

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          Abstract

          Background Robotic-assisted laparoscopic surgery (RALS) is evolving as an important surgical approach in the field of colorectal surgery. We aimed to evaluate the learning curve for RALS procedures involving resections of the rectum and rectosigmoid. Methods A series of 50 consecutive RALS procedures were performed between August 2008 and September 2009. Data were entered into a retrospective database and later abstracted for analysis. The surgical procedures included abdominoperineal resection (APR), anterior rectosigmoidectomy (AR), low anterior resection (LAR), and rectopexy (RP). Demographic data and intraoperative parameters including docking time (DT), surgeon console time (SCT), and total operative time (OT) were analyzed. The learning curve was evaluated using the cumulative sum (CUSUM) method. Results The procedures performed for 50 patients (54% male) included 25 AR (50%), 15 LAR (30%), 6 APR (12%), and 4 RP (8%). The mean age of the patients was 54.4 years, the mean BMI was 27.8 kg/m2, and the median American Society of Anesthesiologists (ASA) classification was 2. The series had a mean DT of 14 min, a mean SCT of 115.1 min, and a mean OT of 246.1 min. The DT and SCT accounted for 6.3% and 46.8% of the OT, respectively. The SCT learning curve was analyzed. The CUSUMSCT learning curve was best modeled as a parabola, with equation CUSUMSCT in minutes equal to 0.73 × case number2 − 31.54 × case number − 107.72 (R = 0.93). The learning curve consisted of three unique phases: phase 1 (the initial 15 cases), phase 2 (the middle 10 cases), and phase 3 (the subsequent cases). Phase 1 represented the initial learning curve, which spanned 15 cases. The phase 2 plateau represented increased competence with the robotic technology. Phase 3 was achieved after 25 cases and represented the mastery phase in which more challenging cases were managed. Conclusions The three phases identified with CUSUM analysis of surgeon console time represented characteristic stages of the learning curve for robotic colorectal procedures. The data suggest that the learning phase was achieved after 15 to 25 cases.

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          Evaluation of the learning curve in laparoscopic colorectal surgery: comparison of right-sided and left-sided resections.

          To provide a multidimensional analysis of the learning curve in major laparoscopic colonic and rectal surgery and compare outcomes between right-sided versus left-sided resections. The laparoscopic learning curve is known to vary between surgeons, may be influenced by the patient selection and operative complexity, and requires appropriate case-mix adjustment. This is a descriptive single-center study using routinely collected clinical data from 900 patients undergoing laparoscopic surgery between November 1991 and April 2003. Outcome measures included operation time, conversion rate (CR), and readmission and postoperative complication rates. Multifactorial logistic regression analysis was used to identify patient-, surgeon-, and procedure-related factors associated with conversion of laparoscopic to open surgery. A risk-adjusted Cumulative Sum (CUSUM) model was used for evaluating the learning curve for right and left-sided resections. The conversion rate for right-sided colonic resections was 8.1% (n = 457) compared with 15.3% for left-sided colorectal resections (n = 443). Independent predictors of conversion of laparoscopic to open surgery were the body mass index (BMI) (odds ratio [OR] = 1.07 per unit increase), ASA grade (OR = 1.63 per unit increase), type of resection (left colorectal versus right colonic procedures, OR = 1.5), presence of intra-abdominal abscess (OR = 5.0) or enteric fistula (OR = 4.6), and surgeon's experience (OR 0.9 per 10 additional cases performed). Having adjusted for case-mix, the CUSUM analysis demonstrated a learning curve of 55 cases for right-sided colonic resections versus 62 cases for left-sided resections. Median operative time declined with operative experience (P<0.001). Readmission rates and postoperative complications remained unchanged throughout the series and were not dependent on operative experience. Conversion rates for laparoscopic colectomy are dependent on a multitude of factors that require appropriate adjustment including the learning curve (operative experience) for individual surgeons. The laparoscopic model described can be used as the basis for performance monitoring between or within institutions.
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            Monitoring surgical performance using risk-adjusted cumulative sum charts.

            The cumulative sum (CUSUM) procedure is a graphical method that is widely used for quality monitoring in industrial settings. More recently it has been used to monitor surgical outcomes whereby it 'signals' if sufficient evidence has accumulated that there has been a change in the surgical failure rate. A limitation of the standard CUSUM procedure in this context is that since it is simply based on the observed surgical outcomes, it may signal as a result of changes in the referral pattern, such as an increased proportion of high-risk patients, rather than due to a change in the actual surgical performance. We describe a new CUSUM procedure that adjusts for each patient's pre-operative risk of surgical failure through the use of a likelihood-based scoring method. The procedure is therefore ideally suited for settings where there is a variable mix of patients over time.
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              Telerobotic-Assisted Laparoscopic Right and Sigmoid Colectomies for Benign Disease

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                Author and article information

                Contributors
                +1-713-7900600 , +1-713-7900616 , ehaasmd@houstoncolon.com
                Journal
                Surg Endosc
                Surgical Endoscopy
                Springer-Verlag (New York )
                0930-2794
                1432-2218
                24 August 2010
                24 August 2010
                March 2011
                : 25
                : 3
                : 855-860
                Affiliations
                [1 ]Department of Surgery, VA Pittsburgh Healthcare System, University Drive C, Pittsburgh, PA 15240 USA
                [2 ]Division of Minimally Invasive Colon and Rectal Surgery, Department of Surgery, University of Texas Medical School at Houston, 7900 Fannin Street, Suite 2700, Houston, TX 77054 USA
                [3 ]Division of Minimally Invasive Colon and Rectal Surgery, Department of Surgery, University of Texas Medical School at Houston, Colorectal Surgical Associates Ltd, LLP, 7900 Fannin Street, Suite 2700, Houston, TX 77054 USA
                Article
                1281
                10.1007/s00464-010-1281-x
                3044842
                20734081
                19e7eff0-cf17-442e-a3a7-51a4428a9106
                © The Author(s) 2010
                History
                : 2 February 2010
                : 19 July 2010
                Categories
                Article
                Custom metadata
                © Springer Science+Business Media, LLC 2011

                Surgery
                learning curve,robotic-assisted laparoscopic surgery,rectosigmoid,cumulative sum analysis

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