A Multi-Institutional Study from the US ROPE Consortium Examining Factors Influencing Vascular Surgery Specialization among General Surgery Residents.

BACKGROUND: There remains a progressive projected deficit in the vascular surgery (VS) workforce for decades yet to come. Despite the rise of an expanding integrated VS residency pathway, the fellowship training model remains critical in supporting our future workforce. Therefore, it is imperative to understand the resident and program-specific factors that influence VS specialization among general surgery (GS) residents. METHODS: Data from the US Resident OPerative Experience (ROPE) Consortium, comprising 20 Accreditation Council for Graduate Medical Education (ACGME)-accredited GS residency programs across the United States, were queried for resident demographics and residency program-related details. Logistic regression analysis was used to identify factors associated with VS specialization. RESULTS: From 2010 to 2020, a total of 1343 graduating GS residents were included in the study. Of these, 135 (10.1%) pursued VS fellowship training. Residents pursuing VS were more frequently male (80.7% vs 62.8%, p<0.0001) and younger (median 32 vs 33 yr, p=0.03) compared with other GS residents. Racial and ethnic group, underrepresented in medicine (URiM) status, and international medical graduate (IMG) status were similar between VS and non-VS groups. Residency program-level details were also similar between groups, including program type (university vs community-based), region, size, resident volume, dedicated research experience, and National Institutes of Health funding. Dedicated vascular rotations were common among all GS programs (95.4%), and total months spent on a VS rotation (median 4 vs 4.5 mo, p=0.11) did not differ among residents pursuing VS and all other residents. The presence of a collocated traditional (5+2) VS fellowship (91.1% vs 90.4%, p=0.79) or integrated (0+5) VS residency (56.3% vs 55.0%, p=0.77) were also similar between groups. On multivariate analysis, only male sex (odds ratio 2.34, 95% confidence interval, 1.50-3.81, p<0.001) was associated with pursuing VS fellowship. Factors that did not impact VS specialization included resident age, URiM status, IMG status, program volume, dedicated research experience, or total months spent on a VS rotation. CONCLUSIONS: In this multi-institutional study, we did not find any program-specific factors that influence VS specialization among GS residents. Notably, the presence of a collocated 0+5 residency or 5+2 fellowship program did not appear to deter GS residents from pursuing VS fellowship. These data suggest that individual factors, such as mentorship, may be more impactful in recruiting GS residents to the VS specialty.

Consensus guidelines on the bedside assistant skills required in robotic surgery.

BACKGROUND: While bedside assistants play a critical role in many robotic operations, substantial heterogeneity remains in bedside assistant training pathways. As such, this study aimed to develop consensus guidelines for bedside assistant skills required for team members in robotic operations. METHODS: We designed a study using the Delphi process to develop consensus guidelines around bedside assistant skills. We generated an initial list of bedside assistant skills from the literature, training materials, and expert input. We selected experts for the Delphi process based on prior scholarship in the area of robotic bedside assistant education and experience facilitating robotic bedside assistant training. For each item, respondents specified which robotic team members should have the skill from a list of "basic" bedside assistants, "advanced" bedside assistants, surgeons, surgical technologists, and circulating nurses. We conducted two rounds of the Delphi process and defined 80% agreement as sufficient for consensus. RESULTS: Fourteen experts participated in two rounds of the Delphi process. By the end of the second round, the group had reached consensus on 253 of 305 items (83%). The group determined that "basic" bedside assistants should have 52 skills and that "advanced" bedside assistants should have 60 skills. The group also determined that surgeons should have 54 skills, surgical technologists should have 25 skills, and circulating nurses should have 17 skills. Experts agreed that all participants should have certain communication skills and basic knowledge of aspects of the robotic system. CONCLUSIONS: We developed consensus guidelines on the skills required during robotic surgery by bedside assistants and other team members using the Delphi process. These findings can be used to design training around bedside assistant skills and assess team members to ensure that each team member has the appropriate skills. Hospitals can also use these guidelines to standardize expectations for robotic team members.

Comparing observed and preferred instruction in robotic surgery.

BACKGROUND: The unique setup of robotic surgery challenges the traditional instructional dynamic between surgical learners and teachers. Previous studies have posited difficulties such as reliance on observational learning and ease of takeover. However, we lack understanding of how these instructional challenges manifest and are perceived by learners. Improving instruction has the potential to optimize education and performance in robotic surgery. METHODS: In this qualitative study, we conducted robotic case observations and learner interviews focusing on instruction in robotic surgery. We deductively generated codes in a theory-informed manner after review of the instructional literature in surgery, medicine, and other fields. We applied these codes in a rigorous directed content analysis of field notes and transcripts to identify themes. RESULTS: Thirty-eight faculty, fellows, and residents participated in 10 robotic cases and 20 semistructured interviews. Observed practices on the basis of case observations differed substantially from preferred practices on the basis of interview data. Using 37 codes, we identified 4 main themes related to instruction in robotic surgery: contextualization, individualization, autonomy, and multimodality. We contrasted observed and preferred instruction in each of these areas to generate instructional considerations that may better align preferences and practices. CONCLUSIONS: We observed several suboptimal instructional practices that contradicted preferred ways of learning. We suggested robotic-specific instructional considerations such as using multimodality to promote active learning and to reduce ambiguity. We also provided considerations applicable to all types of surgery, such as to include rationale to promote learning consolidation and to frame operative steps to allow trainees to plan their participation.