Who Makes It to the End?

A Novel Predictive Model for Identifying Surgical Residents at Risk for Attrition

Heather L. Yeo, MD, MHS; Jonathan S. Abelson, MD; Jialin Mao, MD, MS; Frank Lewis, MD; Fabrizio Michelassi, MD; Richard Bell, MD; Art Sedrakyan, MD; Julie A. Sosa, MD, MA

Disclosures

Annals of Surgery. 2017;266(3):499-507. 

In This Article

Abstract and Introduction

Abstract

Objective: We present 8-year follow-up data from the intern class of 2007 to 2008 using a novel, nonparametric predictive model to identify those residents who are at greatest risk of not completing their training.

Background: Nearly 1 in every 4 categorical general surgery residents does not complete training. There has been no study at a national level to identify individual resident and programmatic factors that can be used to accurately anticipate which residents are most at risk of attrition out.

Methods: A cross-sectional survey of categorical general surgery interns was conducted between June and August 2007. Intern data including demographics, attendance at US or Canadian medical school, proximity of family members, and presence of family members in medicine were de-identified and linked with American Board of Surgery data to determine residency completion and program characteristics. A Classification and Regression Tree analysis was performed to identify groups at greatest risk for non-completion.

Results: Of 1048 interns, 870 completed the initial survey (response rate 83%), 836 of which had linkage data (96%). Also, 672 residents had evidence of completion of residency (noncompletion rate 20%). On Classification and Regression Tree analysis, sex was the independent factor most strongly associated with attrition. The lowest noncompletion rate for men was among interns at small community programs who were White, non-Hispanic, and married (6%). The lowest noncompletion rate for women was among interns training at smaller academic programs (11%).

Conclusions: This is the first longitudinal cohort study to identify factors at the start of training that put residents at risk for not completing training. Data from this study offer a method to identify interns at higher risk for attrition at the start of training, and next steps would be to create and test interventions in a directed fashion.

Introduction

High rates of attrition have plagued graduate surgical education since the elimination of the pyramidal system in 1982, and they remain a problem despite the Accreditation Council for Graduate Medical Education (ACGME) work hour limitations set in place in 2003 and revised in 2011.[1–3] Nearly 1 in every 4 categorical general surgery residents does not complete training. This is particularly concerning, given that there is a national shortage of surgeons in the United States.[4] In addition, attrition has created problems for residency programs, and also for the trainees who spend time in graduate surgical training, only to fall short of finishing residency and entering clinical practice.[5–9]

Almost certainly, some attrition is appropriate; in the end, some who anticipate careers in surgery are poorly suited for the specialty and recognize this after they have started training. However, the attrition rate in surgery is much higher than for most other medical and surgical specialties, including Internal Medicine, Obstetrics and Gynecology, Orthopedics, Ophthalmology, and Otolaryngology; all have attrition rates under 10%.[9–16] Several studies have evaluated predictors of surgical attrition, including personal relationships, training program location, lifestyle concerns, children, and perceptions of poor reimbursement. These factors remain poorly understood, particularly from the perspective of the trainee.[1,17] Single institution and retrospective studies have defined characteristics of trainees that appear to expose them to increased risk for attrition, such as sex, lifestyle concerns, and lack of mentorship.[1,6,7,18–20] To date, however, there has been no study at a national level that has been able to identify individual resident and programmatic factors that, taken together, can be used to accurately anticipate which residents are most at risk of noncompletion, and therefore most likely to benefit from early interventions intended to anticipate and reduce attrition.

In 2007, the prospective National Study on the Expectations and Attitudes of Residents in Surgery (NEARS) was organized to identify those trainees most at risk for attrition.[9] Here, we present 8-year follow-up data from the intern class of 2007 to 2008 using a novel, nonparametric predictive model to identify those residents who are at greatest risk of not completing their training.

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