Learning curve for robotic-assisted laparoscopic colorectal surgery.

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/m(2), 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 CUSUM(SCT) learning curve was best modeled as a parabola, with equation CUSUM(SCT) in minutes equal to 0.73 × case number(2) - 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.

An analysis of the effects of a peer mentor program and other factors on HIV patients' retention in care and clinical outcomes at Thomas Street Health Clinic, Houston Texas

Research examining programs designed to retain patients in health care focus on repeated interactions between outreach workers and patients (Bradford et al. 2007; Cheever 2007). The purpose of this study was to determine if patients who are peer-mentored at their intake exam remain in care longer and attend more physicians' visits than those who were not mentored. Using patients' medical records and a previously created mentor database, the study determined how many patients attended their intake visit but subsequently failed to establish regular care. The cohort study examined risk factors for establishing care, determined if patients lacking a peer mentor failed to establish care more than peer mentor assisted patients, and subsequently if peer mentored patients had better health outcomes. The sample consists of 1639 patients who were entered into the Thomas Street Patient Mentor Database between May 2005 and June 2007. The assignment to the mentored group was haphazardly conducted based on mentor availability. The data from the Mentor Database was then analyzed using descriptive statistical software (SPSS version 15; SPSS Inc., Chicago, Illinois, USA). Results indicated that patients who had a mentor at intake were more likely to return for primary care HIV visits at 90 and 180 days. Mentored patients also were more likely to be prescribed ART within 180 days from intake. Other risk factors that impacted remaining in care included gender, previous care status, time from diagnosis to intake visit, and intravenous drug use. Clinical health outcomes did not differ significantly between groups. This supports that mentoring did improve outcomes. Continuing to use peer-mentoring programs for HIV care may help in increasing retention of patients in care and improving patients' health in a cost effective manner. Future research on the effects of peer mentoring on mentors, and effects of concordance of mentor and patient demographics may help to further improve peer-mentoring programs. ^