Jennifer Chung1, Andrea Obi2, Ryan Chen3, Wandi Lin3, Siyuan Sun3, Zixiao Chen3, Anurag Gulati3, Xun Xu3, William Pozehl3, F Jacob Seagull1, Amy M Cohn4, Mark S Daskin3, Rishindra M Reddy5. 1. University of Michigan Medical School, Ann Arbor, Michigan. 2. Department of Surgery, University of Michigan, Ann Arbor, Michigan. 3. Department of Industrial and Operations Engineering, University of Michigan, Ann Arbor, Michigan. 4. Department of Industrial and Operations Engineering, University of Michigan, Ann Arbor, Michigan; Center for Healthcare Engineering and Patient Safety, Ann Arbor, Michigan. 5. University of Michigan Medical School, Ann Arbor, Michigan; Department of Surgery, University of Michigan, Ann Arbor, Michigan. Electronic address: reddyrm@med.umich.edu.
Abstract
INTRODUCTION: Work-hour restrictions have decreased flexibility in scheduling and reduced exposure to certain operative cases. These restrictions may affect a resident's ability to meet certification requirements, particularly for rare, unscheduled cases (e.g., cardiothoracic transplants). We developed a computer-based simulation model using variables such as case volume and program size to demonstrate the influence of these factors on the likelihood of certifying a set of residents on rare cases. METHODS: We built a simulator to predict the probability of attaining certification for surgical residents, using cardiothoracic transplants as a test case. Inputs to the model included operating times, call schedules, and procurement travel times, as well as information on the distribution of times between transplants. RESULTS: We simulated 100 years of schedules using our current system parameters of an average of 33 heart and 31 lung transplants per year, and assuming an Accreditation Council for Graduate Medical Education-compliant daily-rotating call schedule. Despite having enough transplants to certify all residents for lungs if all opportunities were distributed equally among residents, the certification rate achieved when constrained by arrival time (and call schedules) and work restrictions was only 55%. Our calculations show that meeting minimum transplant-certification requirements for all residents would require at least 1.5 times the expected number of annual transplants. CONCLUSIONS: Our model enables analysis of a given program's ability to certify its residents based on program size and volume. These results could be used to design alternative scheduling paradigms to improve certification rates, without requiring reductions in certification requirements or program size.
INTRODUCTION: Work-hour restrictions have decreased flexibility in scheduling and reduced exposure to certain operative cases. These restrictions may affect a resident's ability to meet certification requirements, particularly for rare, unscheduled cases (e.g., cardiothoracic transplants). We developed a computer-based simulation model using variables such as case volume and program size to demonstrate the influence of these factors on the likelihood of certifying a set of residents on rare cases. METHODS: We built a simulator to predict the probability of attaining certification for surgical residents, using cardiothoracic transplants as a test case. Inputs to the model included operating times, call schedules, and procurement travel times, as well as information on the distribution of times between transplants. RESULTS: We simulated 100 years of schedules using our current system parameters of an average of 33 heart and 31 lung transplants per year, and assuming an Accreditation Council for Graduate Medical Education-compliant daily-rotating call schedule. Despite having enough transplants to certify all residents for lungs if all opportunities were distributed equally among residents, the certification rate achieved when constrained by arrival time (and call schedules) and work restrictions was only 55%. Our calculations show that meeting minimum transplant-certification requirements for all residents would require at least 1.5 times the expected number of annual transplants. CONCLUSIONS: Our model enables analysis of a given program's ability to certify its residents based on program size and volume. These results could be used to design alternative scheduling paradigms to improve certification rates, without requiring reductions in certification requirements or program size.
Keywords:
Medical Knowledge; Practice-Based Learning and Improvement; Scheduling; Systems-Based Practice; graduate medical education; surgery; transplant
Authors: Tyler R Grenda; Tiffany N S Ballard; Andrea T Obi; William Pozehl; F Jacob Seagull; Ryan Chen; Amy M Cohn; Mark S Daskin; Rishindra M Reddy Journal: J Grad Med Educ Date: 2016-12