Readiness of US General Surgery Residents for Independent Practice
University of Michigan1, Harvard University2, Indiana University3, Northwestern University4, State University of New York Upstate Medical University5, University of Washington6, University of Minnesota7, University of New Mexico8, Vanderbilt University9, Washington University in St. Louis10, University of Texas Southwestern Medical Center11, University of Wisconsin-Madison12, University of Kentucky13
TL;DR: US General Surgery residents are not universally ready to independently perform Core procedures by the time they complete residency training, and it is unknown if the amount of autonomy residents do achieve is sufficient to ensure readiness for the entire spectrum of independent practice.
Abstract: Objective:This study evaluates the current state of the General Surgery (GS) residency training model by investigating resident operative performance and autonomy.Background:The American Board of Surgery has designated 132 procedures as being “Core” to the practice of GS. GS residents are expected t
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TL;DR: This adequately powered, randomized controlled trial demonstrated how an immersive VR system can efficiently teach a complex surgical procedure and also demonstrate improved translational skill and knowledge acquisition when compared with a traditional learning method.
Abstract: BACKGROUND There has been limited literature on immersive virtual reality (VR) simulation in orthopaedic education. The purpose of this multicenter, blinded, randomized controlled trial was to determine the validity and efficacy of immersive VR training in orthopaedic resident education. METHODS Nineteen senior orthopaedic residents (resident group) and 7 consultant shoulder arthroplasty surgeons (expert group) participated in the trial comparing immersive VR with traditional learning using a technical journal article as a control. The examined task focused on achieving optimal glenoid exposure. Participants completed demographic questionnaires, knowledge tests, and a glenoid exposure on fresh-frozen cadavers while being examined by blinded shoulder arthroplasty surgeons. Training superiority was determined by the outcome measures of the Objective Structured Assessment of Technical Skills (OSATS) score, a developed laboratory metric, verbal answers, and time to task completion. RESULTS Immersive VR had greater realism and was superior in teaching glenoid exposure than the control (p = 0.01). The expert group outperformed the resident group on knowledge testing (p = 0.04). The immersive VR group completed the learning activity and knowledge tests significantly faster (p < 0.001) at a mean time (and standard deviation) of 11 ± 3 minutes than the control group at 20 ± 4 minutes, performing 3 to 5 VR repeats for a reduction in learning time of 570%. The immersive VR group completed the glenoid exposure significantly faster (p = 0.04) at a mean time of 14 ± 7 minutes than the control group at 21 ± 6 minutes, with superior OSATS instrument handling scores (p = 0.03). The immersive VR group scored equivalently in surprise verbal scores (p = 0.85) and written knowledge scores (p = 1.0). CONCLUSIONS Immersive VR demonstrated substantially improved translational technical and nontechnical skills acquisition over traditional learning in senior orthopaedic residents. Additionally, the results demonstrate the face, content, construct, and transfer validity for immersive VR. CLINICAL RELEVANCE This adequately powered, randomized controlled trial demonstrated how an immersive VR system can efficiently (570%) teach a complex surgical procedure and also demonstrate improved translational skill and knowledge acquisition when compared with a traditional learning method.
71 citations
Northwestern University1, University of Michigan2, Indiana University3, Harvard University4, University of Washington5, University of Texas Southwestern Medical Center6, University of Wisconsin-Madison7, University of Nebraska Medical Center8, University of New Mexico9, University of Minnesota10, State University of New York Upstate Medical University11, Vanderbilt University12, Washington University in St. Louis13, University of Kentucky14
TL;DR: It is concluded that procedural target numbers are generally not effective in predicting procedural competence and should not be used as the basis for determining residents' readiness for independent practice.
62 citations
University of Colorado Boulder1, Northwestern University2, Washington University in St. Louis3, Boston Children's Hospital4, Brigham and Women's Hospital5, Stanford University6, University of North Carolina at Chapel Hill7, Mayo Clinic8, University of Wisconsin-Madison9, Stony Brook University10, University Hospitals of Cleveland11, University of California, Los Angeles12, Cleveland Clinic13, Medical University of South Carolina14, Icahn School of Medicine at Mount Sinai15, Carolinas Medical Center16, Thomas Jefferson University17, Indiana University – Purdue University Indianapolis18, Dartmouth–Hitchcock Medical Center19, Vanderbilt University20, Virginia Mason Medical Center21, University of South Florida22, Duke University23, University of Alberta24, University of Pennsylvania25, University of Michigan26, University of Kansas27, Henry Ford Hospital28, Columbia University29, University of California, Davis30, University of Massachusetts Amherst31, University of Texas Southwestern Medical Center32, University of Virginia33
TL;DR: It is found that although competence cannot be confirmed for all AETs at the end of training, most meet QI thresholds for EUS and ERCP at theend of their first year of independent practice, which affirms the effectiveness of training programs.
56 citations
TL;DR: Virtual reality training was more effective than a passive SG in the authors' model of simulated tibia IMN for novice medical students, and may be a useful method to augment orthopedic education.
56 citations
References
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TL;DR: The brms package implements Bayesian multilevel models in R using the probabilistic programming language Stan, allowing users to fit linear, robust linear, binomial, Poisson, survival, ordinal, zero-inflated, hurdle, and even non-linear models all in a multileVEL context.
Abstract: The brms package implements Bayesian multilevel models in R using the probabilistic programming language Stan. A wide range of distributions and link functions are supported, allowing users to fit - among others - linear, robust linear, binomial, Poisson, survival, ordinal, zero-inflated, hurdle, and even non-linear models all in a multilevel context. Further modeling options include autocorrelation of the response variable, user defined covariance structures, censored data, as well as meta-analytic standard errors. Prior specifications are flexible and explicitly encourage users to apply prior distributions that actually reflect their beliefs. In addition, model fit can easily be assessed and compared with the Watanabe-Akaike information criterion and leave-one-out cross-validation.
4,353 citations
01 Jan 2017
TL;DR: Stan is a probabilistic programming language for specifying statistical models that provides full Bayesian inference for continuous-variable models through Markov chain Monte Carlo methods such as the No-U-Turn sampler and an adaptive form of Hamiltonian Monte Carlo sampling.
Abstract: Stan is a probabilistic programming language for specifying statistical models. A Stan program imperatively defines a log probability function over parameters conditioned on specified data and constants. As of version 2.14.0, Stan provides full Bayesian inference for continuous-variable models through Markov chain Monte Carlo methods such as the No-U-Turn sampler, an adaptive form of Hamiltonian Monte Carlo sampling. Penalized maximum likelihood estimates are calculated using optimization methods such as the limited memory Broyden-Fletcher-Goldfarb-Shanno algorithm. Stan is also a platform for computing log densities and their gradients and Hessians, which can be used in alternative algorithms such as variational Bayes, expectation propagation, and marginal inference using approximate integration. To this end, Stan is set up so that the densities, gradients, and Hessians, along with intermediate quantities of the algorithm such as acceptance probabilities, are easily accessible. Stan can be called from the command line using the cmdstan package, through R using the rstan package, and through Python using the pystan package. All three interfaces support sampling and optimization-based inference with diagnostics and posterior analysis. rstan and pystan also provide access to log probabilities, gradients, Hessians, parameter transforms, and specialized plotting.
2,938 citations
TL;DR: Assessment of general surgery graduate trainees entering accredited surgical subspecialty fellowships in North America revealed deficits in domains of operative autonomy, progressive responsibility, longitudinal follow-up, and scholarly focus after general surgery education.
Abstract: Objective:To assess readiness of general surgery graduate trainees entering accredited surgical subspecialty fellowships in North America.Methods:A multidomain, global assessment survey designed by the Fellowship Council research committee was electronically sent to all subspecialty program director
641 citations
"Readiness of US General Surgery Res..." refers background in this paper
...National surveys have demonstrated that these concerns are widespread.(4,5) Residents themselves sometimes feel less than fully confident, which may explain the rising rates of graduates seeking additional fellowship training....
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...The best evidence in this regard comes from a survey of programs directors performed by Mattar et al in 2012.(4) In that research, 26....
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TL;DR: The authors distinguish different modes of trust and entrustment decisions and elaborate five categories, each with related factors, that determine when decisions to trust trainees are made: the trainee, supervisor, situation, task, and the relationship between trainee and supervisor.
Abstract: The decision to trust a medical trainee with the critical responsibility to care for a patient is fundamental to clinical training. When carefully and deliberately made, such decisions can serve as significant stimuli for learning and also shape the assessment of trainees. Holding back entrustment decisions too much may hamper the trainee's development toward unsupervised practice. When carelessly made, however, they jeopardize patient safety. Entrustment decision-making processes, therefore, deserve careful analysis.Members (including the authors) of the International Competency-Based Medical Education Collaborative conducted a content analysis of the entrustment decision-making process in health care training during a two-day summit in September 2013 and subsequently reviewed the pertinent literature to arrive at a description of the critical features of this process, which informs this article.The authors discuss theoretical backgrounds and terminology of trust and entrustment in the clinical workplace. The competency-based movement and the introduction of entrustable professional activities force educators to rethink the grounds for assessment in the workplace. Anticipating a decision to grant autonomy at a designated level of supervision appears to align better with health care practice than do most current assessment practices. The authors distinguish different modes of trust and entrustment decisions and elaborate five categories, each with related factors, that determine when decisions to trust trainees are made: the trainee, supervisor, situation, task, and the relationship between trainee and supervisor. The authors' aim in this article is to lay a theoretical foundation for a new approach to workplace training and assessment.
326 citations
TL;DR: The aim of this systematic review was to identify and evaluate the application and effectiveness of quality improvement methodologies to the field of surgery.
Abstract: Background:
The demand for the highest-quality patient care coupled with pressure on funding has led to the increasing use of quality improvement (QI) methodologies from the manufacturing industry. The aim of this systematic review was to identify and evaluate the application and effectiveness of these QI methodologies to the field of surgery.
Methods:
MEDLINE, the Cochrane Database, Allied and Complementary Medicine Database, British Nursing Index, Cumulative Index to Nursing and Allied Health Literature, Embase, Health Business™ Elite, the Health Management Information Consortium and PsycINFO® were searched according to the Preferred Reporting Items for Systematic Reviews and Meta-Analyses statement. Empirical studies were included that implemented a described QI methodology to surgical care and analysed a named outcome statistically.
Results:
Some 34 of 1595 articles identified met the inclusion criteria after consensus from two independent investigators. Nine studies described continuous quality improvement (CQI), five Six Sigma, five total quality management (TQM), five plan-do-study-act (PDSA) or plan-do-check-act (PDCA) cycles, five statistical process control (SPC) or statistical quality control (SQC), four Lean and one Lean Six Sigma; 20 of the studies were undertaken in the USA. The most common aims were to reduce complications or improve outcomes (11), to reduce infection (7), and to reduce theatre delays (7). There was one randomized controlled trial.
Conclusion:
QI methodologies from industry can have significant effects on improving surgical care, from reducing infection rates to increasing operating room efficiency. The evidence is generally of suboptimal quality, and rigorous randomized multicentre studies are needed to bring evidence-based management into the same league as evidence-based medicine. Copyright © 2011 British Journal of Surgery Society Ltd. Published by John Wiley & Sons, Ltd.
306 citations