Interview Scores Correlate with Fellow Microsurgical Skill and Performance
14 July 2017
14 September 2017
27 October 2017 (eFirst)
Background The interview process for surgical trainees aims to select those individuals who will perform best during training and have the greatest potential as future surgeons. The objective of this study was to evaluate the relationship between criteria assessed at interview, technical skills, and performance, for the first time, to optimize the selection process for a Microsurgery fellowship.
Methods Twenty microsurgery fellows in three consecutive annual cohorts at a single academic center were prospectively evaluated. At interview, subjects were scored for multiple standardized domains. At the start and at end of the fellowship, microsurgical technical skill was assessed both in the laboratory and operating room (OR) using a validated assessment tool. At the end of the fellowship, there was a final evaluation of performance.
Results At the start, microsurgical skill significantly correlated with almost all domains evaluated at interview, most closely with prior plastic surgery training experience. At the end of the fellowship, skill level improved in all trainees, with the greatest improvement made by the lowest ranked and skilled trainees. The highest ranked trainees, however, made the greatest improvement in speed.
Conclusions The results of this study, for the first time, validate the current interview process to correctly select the highest performing and most skilled candidates and support the effectiveness of a 1-year microsurgical fellowship in improving microsurgical skill in all trainees, irrespective of their initial ability. The importance of valuing the relative quality of prior training and experience at selection is also highlighted.
The study was presented at the American Society for Reconstructive Microsurgery Meeting Outstanding Paper on January 14, 2017 and at the American Society of Plastic Surgeons Meeting on September 26, 2016.
Financial Disclosure Statement
None of the authors has a financial interest in any of the products, devices, or drugs mentioned in this manuscript.
- 1 Daly KA, Levine SC, Adams GL. Predictors for resident success in otolaryngology. J Am Coll Surg 2006; 202 (04) 649-654
- 2 Grewal SG, Yeung LS, Brandes SB. Predictors of success in a urology residency program. J Surg Educ 2013; 70 (01) 138-143
- 3 Oldfield Z, Beasley SW, Smith J, Anthony A, Watt A. Correlation of selection scores with subsequent assessment scores during surgical training. ANZ J Surg 2013; 83 (06) 412-416
- 4 Tolan AM, Kaji AH, Quach C, Hines OJ, de Virgilio C. The electronic residency application service application can predict accreditation council for graduate medical education competency-based surgical resident performance. J Surg Educ 2010; 67 (06) 444-448
- 5 Brothers TE, Wetherholt S. Importance of the faculty interview during the resident application process. J Surg Educ 2007; 64 (06) 378-385
- 6 Cuschieri A, Francis N, Crosby J, Hanna GB. What do master surgeons think of surgical competence and revalidation?. Am J Surg 2001; 182 (02) 110-116
- 7 Gallagher AG, Neary P, Gillen P. , et al. Novel method for assessment and selection of trainees for higher surgical training in general surgery. ANZ J Surg 2008; 78 (04) 282-290
- 8 Carroll SM, Kennedy AM, Traynor O, Gallagher AG. Objective assessment of surgical performance and its impact on a national selection programme of candidates for higher surgical training in plastic surgery. J Plast Reconstr Aesthet Surg 2009; 62 (12) 1543-1549
- 9 The Accreditation Council for Graduate Medical Education. Available at: https://www.acgme.org . Accessed on 1st July 2017
- 10 Selber JC, Tong W, Koshy J, Ibrahim A, Liu J, Butler C. Correlation between trainee candidate selection criteria and subsequent performance. J Am Coll Surg 2014; 219 (05) 951-957
- 11 Selber JC, Chang EI, Liu J. , et al. Tracking the learning curve in microsurgical skill acquisition. Plast Reconstr Surg 2012; 130 (04) 550e-557e
- 12 Alrasheed T, Liu J, Hanasono MM, Butler CE, Selber JC. Robotic microsurgery: validating an assessment tool and plotting the learning curve. Plast Reconstr Surg 2014; 134 (04) 794-803
- 13 Chan W, Niranjan N, Ramakrishnan V. Structured assessment of microsurgery skills in the clinical setting. J Plast Reconstr Aesthet Surg 2010; 63 (08) 1329-1334
- 14 Random Number Order Generator. Available at: https://www.random.org/lists
- 15 Mukaka MM. Statistics corner: a guide to appropriate use of correlation coefficient in medical research. Malawi Med J 2012; 24 (03) 69-71
- 16 Cicchetti DV. Guidelines, criteria, and rules of thumb for evaluating normed and standardized assessment instruments in psychology. Psychol Assess 1994; 6 (01) 284-290
- 17 Schaverien MV. Selection for surgical training: an evidence-based review. J Surg Educ 2016; 73 (04) 721-729
- 18 Chole RA, Ogden MA. Predictors of future success in otolaryngology residency applicants. Arch Otolaryngol Head Neck Surg 2012; 138 (08) 707-712
- 19 Grantcharov TP, Reznick RK. Training tomorrow's surgeons: what are we looking for and how can we achieve it?. ANZ J Surg 2009; 79 (03) 104-107
- 20 Funk DI, Ronai AK, Kinzer JB, Barrett MJ. Personality traits in anesthesia resident evaluations. Anesthesiology 1984; 61 (01) 462
- 21 Tarico V, Smith WL, Altmaier E, Franken EA, Van Velzen D. Critical incident interviewing in evaluation of resident performance. Radiology 1984; 152 (02) 327-329
- 22 Altmaier E, Smith WL, Wood P. , et al. Cross-institutional stability of behavioral criteria desirable for success in radiology residency. Invest Radiol 1989; 24 (03) 249-251
- 23 Smith WL, Berbaum KS. Improving resident selection. Discrimination by perceptual abilities. Invest Radiol 1991; 26 (10) 910-912
- 24 Altmaier EM, Smith WL, O'Halloran CM, Franken Jr EA. The predictive utility of behavior-based interviewing compared with traditional interviewing in the selection of radiology residents. Invest Radiol 1992; 27 (05) 385-389
- 25 Park E, Ha PK, Eisele DW, Francis HW, Kim YJ. Personal characteristics of residents may predict competency improvement. Laryngoscope 2016; 126 (08) 1746-1752
- 26 Louridas M, Szasz P, de Montbrun S, Harris KA, Grantcharov TP. Can we predict technical aptitude? A systematic review. Ann Surg 2016; 263 (04) 673-691
- 27 Beard JD, Marriott J, Purdie H, Crossley J. Assessing the surgical skills of trainees in the operating theatre: a prospective observational study of the methodology. Health Technol Assess 2011; 15 (01) i-xxi , 1–162
- 28 Yule S, Paterson-Brown S. Surgeons' non-technical skills. Surg Clin North Am 2012; 92 (01) 37-50