Gender Disparities in General Surgery Resident Subspecialization.

BACKGROUND: There are an increasing number of women entering medical school and general surgery residency. Despite this, there remains an underrepresentation of women in some surgical specialties. The purpose of this study is to examine gender differences in fellowship subspecialization of recent general surgery graduates. METHODS: Graduating residents from general surgery residencies from 2016 to 2020 were identified. Referring to each residency's graduating resident website, we noted whether or not listed alumni were reported to have entered a fellowship. If applicants were listed as having completed a fellowship, the fellowship was noted along with each applicant's expressed gender. Differences across groups were analyzed using SPSS. RESULTS: The majority (82.4%) of graduates pursued a fellowship after residency training. Men were more likely to enter fellowships in Cardiothoracic Surgery, Plastic and Reconstructive Surgery, Vascular Surgery, and practice than women. Women were more likely to enter fellowships in Breast Surgery, Acute Care Surgery/Trauma Surgery, Pediatric Surgery, and Endocrine Surgery than men. CONCLUSIONS: The majority of general surgery residency graduates pursue fellowship training. Gender disparities continue for a minority of subspecialties for both men and women.

Robotic simulation: validation and qualitative assessment of a general surgery resident training curriculum.

BACKGROUND: The da Vinci skills simulation curriculum has been validated in the literature. The updated simulator, SimNow, features restructured exercises that have not been formally validated. The purpose of this study is to validate the SimNow resident robotic basic simulation curriculum. This study also consists of a qualitative assessment that gives greater insight into the learner's experience completing the robotic curriculum. METHODS: There were 18 participants in this study: 6 novices, 6 competent surgeons, and 6 expert surgeons. The curriculum comprised 5 exercises; participants completed three consecutive scored trials. Computer-derived performance metrics were recorded. The NASA Task Load Index survey was used to assess subjective mental workload. Subjects were asked a series of open-ended questions regarding their experience that were recorded and transcribed. Codes were identified using an inductive method, and themes were generated. RESULTS: Performance metrics were significantly different between novice versus competent and expert surgeons. There was no significant difference in any score metric between competent and expert surgeons. On average, overall score percentages for competent and expert surgeons were between 90.4 and 92.8% versus 70.5% for novices (p = 0.02 and p = 0.01). Expert surgeons perceived a higher level of performance completing the exercises than novice surgeons (15.8 vs. 45.8, p = 0.02). Participants noted a similar robotic experience, utilizing efficiency of motion and visual field skills. Participants agreed on exercise strengths, exercise weaknesses, and software limitations. Competent and expert surgeons were better able to assess the exercises' clinical application. CONCLUSIONS: The SimNow curriculum is a valid simulation training as part of a general surgery resident robotic curriculum. The curriculum distinguishes between novices compared to competent and expert surgeons, but not between competent and expert surgeons. Clinical training level does not affect the experience and mental workload using the robotic simulator, except for competent and expert surgeons' ability to better assess clinical application.

Defining benchmarks for fellowship training in foregut surgery: a 10-year review of fellowship council index cases.

INTRODUCTION: Surgical treatment of foregut disease is a complex field that demands advanced expertise to ensure favorable outcomes for patients. To address the growing need for foregut surgeons, leaders within several national societies have become interested in developing a foregut fellowship. The aim of this study was to develop data-driven benchmarks that will aid in defining appropriate accreditation criteria for these fellowships. METHODS: We obtained case log data for Fellowship Council fellows trained from 2009-2019. We identified 78 complex foregut (non-bariatric) case codes and divided them into 5 index case categories including (1) hiatal/paraoesophageal hernia repair, (2) fundoplication, (3) esophageal myotomy, (4) major organ resection, and (5) minor organ resection. Median volumes in each index category were compared over time using Kruskall-Wallis tests. The share of cases done using open, laparoscopic, or robotic approaches were analyzed using linear regression analysis. RESULTS: For the 10 years analyzed, 1362 fellows logged 82,889 operations and 111,799 endoscopies. Median foregut cases per fellow grew significantly from 42 (IQR = 24-74) cases in 2010 to 69 (IQR = 33-106) cases in 2019. Median endoscopy volumes also grew significantly from 42 (IQR = 7-88) in 2010 to 69 (IQR 32-123) in 2019.The volume of hiatal/paraoesophageal hernia repairs increased significantly over time while volumes in the remaining 4 index categories remained stable. The share of robotic cases exhibited near perfect linear growth from 2.2% of all foregut cases in 2010 to 14.4% in 2019 (R = 0.99, p < 0.0001). Open cases exhibited linear decay from 7.2% of cases in 2010 to 4.7% of cases in 2019 (R = 0.92, p = 0.0001). Laparoscopic/thoracoscopic cases also exhibited linear decay from 90.6% of cases in 2010 to 80.9% of cases in 2019 (R = 0.98, p < 0.00001). CONCLUSIONS: FC fellows are exposed to robust volumes of foregut cases. This rich data set provides an evidence-based guide for establishing criteria for potential foregut fellowships.