Residency Milestones Predict Performance in Vascular Surgery Fellowship

Standardizing the Educational Hand-off in Surgical Training

The transition from generalist residency to subspecialty fellowship represents a critical juncture where a seamless transfer of clinical competency is essential for patient safety, particularly in high-acuity fields like vascular surgery. While clinical practice relies on evidence-based guidelines to manage high-risk conditions [1, 2], and research protocols are standardized to ensure transparency [3], the educational hand-off between training programs often lacks a similar structure. This gap can leave fellowship directors without objective data on a new trainee's specific strengths or areas needing development, a significant concern in specialties where precise execution is vital [4, 5]. Establishing a reliable continuum of assessment is therefore crucial for maintaining rigorous standards. A recent study now examines whether standardized residency evaluations can predict performance during the first year of subspecialty fellowship, offering a potential framework for this hand-off.

Quantifying the Continuum of Surgical Competency

To investigate the link between residency and fellowship performance, researchers conducted a retrospective national study of the educational transition from general surgery to vascular surgery. The analysis included two cohorts of vascular surgery fellows (n=266) who began their training in 2022 and 2023, all of whom had previously completed a general surgery residency. This design provided a consistent foundation for tracking trainee development across distinct stages of surgical education. The study's core data came from the Accreditation Council for Graduate Medical Education (ACGME) Milestones 2.0, a standardized framework for assessing key clinical skills. The researchers compared ratings from the final two years of each surgeon's residency with their ratings from the first year of fellowship. To analyze the relationship, they used linear mixed effects regression models, a statistical method that isolates the predictive relationship between two variables while accounting for individual variations among trainees over time. This approach allowed the authors to quantify how closely a trainee's residency ratings correlated with their subsequent achievement as a first-year fellow, potentially identifying early signals for learners who may require additional support.

Predictive Value of Core Clinical Domains

The analysis revealed a statistically significant correlation between performance in the final year of general surgery residency and achievement during the first year of vascular surgery fellowship across four core competency domains. The study found significant predictive alignment for Patient Care (PC), with a beta coefficient of β=0.20 (P=0.004). A beta coefficient is a statistical value that indicates how strongly one variable predicts another; in this case, how well residency scores forecasted fellowship scores. Similar predictive relationships were observed for Medical Knowledge (MK) (β=0.13, P=0.027) and Interpersonal and Communication Skills (ICS) (β=0.17, P=0.01). The strongest correlation was found in the domain of Professionalism (PROF), which showed a β=0.23 (P<0.001), suggesting that professional conduct is a highly consistent trait across the training continuum. These findings indicate that proficiency in these fundamental areas during residency serves as a reliable indicator of a trainee's initial clinical trajectory in subspecialty training. The study also quantified the practical impact of these correlations. For every 1-unit difference in Milestones ratings between general surgery residents, the data showed a corresponding mean fellowship Milestones level difference of 0.49 to 0.64 units. This suggests that roughly half to two-thirds of a performance gap observed at the end of residency persists into the first year of fellowship. For clinical educators, this provides a data-driven basis for implementing targeted interventions and early feedback to support trainees who may be at risk of struggling during this critical professional transition.

Granular Alignment Across Subcompetencies

Delving deeper, the researchers analyzed specific clinical skills, or subcompetencies, nested within the broader domains. The most consistent alignment was found in Professionalism (PROF), where all 4 of 4 matched subcompetencies were significantly correlated between residency and fellowship. This reinforces that a trainee's ethical conduct and accountability are stable attributes. Similarly, Medical Knowledge (MK) showed significant alignment in both of its 2 matched subcompetencies, indicating that the foundational knowledge base from residency directly supports fellowship-level work. In more applied domains, the predictive value remained strong but showed some variation. Patient Care (PC) demonstrated significant alignment in 3 of 4 subcompetencies, while Interpersonal and Communication Skills (ICS) showed alignment in 2 of 3 subcompetencies. These results suggest that while most clinical and communication skills transfer predictably, certain specific tasks may evolve in complexity in the specialized vascular surgery environment. Conversely, the study identified two domains where residency performance did not predict fellowship outcomes. Ratings for Systems-Based Practice (SBP), which assesses a trainee's ability to navigate the broader healthcare system, were not significantly aligned. Likewise, Practice-Based Learning and Improvement (PBLI) ratings, which measure the ability to use evidence to improve one's own patient care, also showed no significant alignment. This lack of correlation may suggest that the institutional workflows and self-improvement demands of a subspecialty fellowship are distinct enough from general surgery that all trainees must adapt, regardless of prior performance in these areas.

Implications for Early Intervention and Mentorship

This study establishes that the transition from general surgery residency to vascular surgery fellowship is a measurable progression rather than a disconnected leap. The alignment between graduating resident and first-year fellow ratings in Patient Care, Medical Knowledge, Professionalism, and Interpersonal and Communication Skills demonstrates a clear continuum in educational outcomes. This continuity provides fellowship directors with objective, data-driven insights into an incoming trainee's capabilities, moving beyond subjective letters of recommendation. The primary clinical application of these findings is the potential to identify and support struggling learners earlier and more effectively. The authors propose that Milestones 2.0 data can facilitate a structured residency-to-fellowship hand-off through performance analytics, which involves using statistical tracking to anticipate a learner's trajectory. Because the data showed strong predictive alignment in core domains like Professionalism (β=0.23, P<0.001), fellowship directors can use residency exit ratings to flag individuals who may benefit from additional mentorship or targeted educational support from day one. This proactive approach enables early feedback, ensuring the high-stakes transition into a surgical subspecialty is supported by a structured framework designed to foster success.

References

1. Collaboration AT. Collaborative meta-analysis of randomised trials of antiplatelet therapy for prevention of death, myocardial infarction, and stroke in high risk patients. BMJ. 2002. doi:10.1136/bmj.324.7329.71

2. Collet J, Thiele H, Barbato E, et al. 2020 ESC Guidelines for the management of acute coronary syndromes in patients presenting without persistent ST-segment elevation. European Heart Journal. 2020. doi:10.1093/eurheartj/ehaa575

3. Chan A, Tetzlaff J, Gøtzsche PC, et al. SPIRIT 2013 explanation and elaboration: guidance for protocols of clinical trials. BMJ. 2013. doi:10.1136/bmj.e7586

4. Williams B, Mancia G, Spiering W, et al. 2018 ESC/ESH Guidelines for the management of arterial hypertension. European Heart Journal. 2018. doi:10.1093/eurheartj/ehy339

5. Joglar JA, Chung MK, Armbruster AL, et al. 2023 ACC/AHA/ACCP/HRS Guideline for the Diagnosis and Management of Atrial Fibrillation: A Report of the American College of Cardiology/American Heart Association Joint Committee on Clinical Practice Guidelines. Circulation. 2023. doi:10.1161/cir.0000000000001193