title: The electronic residency application service application can predict accreditation council for graduate medical education competency-based surgical resident performance.
abstract: OBJECTIVE
  Program directors often struggle to determine which factors in the Electronic Residency Application Service (ERAS) application are important in the residency selection process. With the establishment of the Accreditation Council for Graduate Medical Education (ACGME) competencies, it would be important to know whether information available in the ERAS application can predict subsequent competency-based performance of general surgery residents.
  
  
  METHODS
  This study is a retrospective correlation of data points found in the ERAS application with core competency-based clinical rotation evaluations. ACGME competency-based evaluations as well as technical skills assessment from all rotations during residency were collected. The overall competency score was defined as an average of all 6 competencies and technical skills.
  
  
  RESULTS
  A total of77 residents from two (one university and one community based university-affiliate) general surgery residency programs were included in the analysis. Receiving honors for many of the third year clerkships and AOA membership were associated with a number of the individual competencies. USMLE scores were predictive only of Medical Knowledge (p = 0.004). Factors associated with higher overall competency were female gender (p = 0.02), AOA (p = 0.06), overall number of honors received (p = 0.04), and honors in Ob/Gyn (p = 0.03) and Pediatrics (p = 0.05). Multivariable analysis showed honors in Ob/Gyn, female gender, older age, and total number of honors to be predictive of a number of individual core competencies. USMLE scores were only predictive of Medical Knowledge.
  
  
  CONCLUSIONS
  The ERAS application is useful for predicting subsequent competency based performance in surgical residents. Receiving honors in the surgery clerkship, which has traditionally carried weight when evaluating a potential surgery resident, may not be as strong a predictor of future success.
authors.affiliation: Department of Surgery, Harbor-UCLA Medical Center, Torrance, California 90509, USA.
authors.forename: Amy M
authors.initials: AM
authors.lastname: Tolan
authors.forename: Amy H
authors.initials: AH
authors.lastname: Kaji
authors.forename: Chi
authors.initials: C
authors.lastname: Quach
authors.forename: O Joe
authors.initials: OJ
authors.lastname: Hines
authors.forename: Christian
authors.initials: C
authors.lastname: de Virgilio
mesh_terms: D000068:Accreditation; D000328:Adult; D002983:Clinical Competence; D003162:Competency-Based Education; D004503:Education, Medical, Graduate / Q000379:methods; D001330:Electronic Data Processing; D005260:Female; D013502:General Surgery / Q000193:education*; D006801:Humans; D007396:Internship and Residency / Q000706:statistics & numerical data*; D007586:Job Application; D008297:Male; D015999:Multivariate Analysis; D010560:Personnel Selection; D011237:Predictive Value of Tests; D012189:Retrospective Studies