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Using optimization models to demonstrate the need for structural changes in training programs for surgical medical residents

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  • Jonathan Turner
  • Kibaek Kim
  • Sanjay Mehrotra
  • Debra DaRosa
  • Mark Daskin
  • Heron Rodriguez

Abstract

The primary goal of a residency program is to prepare trainees for unsupervised care. Duty hour restrictions imposed throughout the prior decade require that residents work significantly fewer hours. Moreover, various stakeholders (e.g. the hospital, mentors, other residents, educators, and patients) require them to prioritize very different activities, often conflicting with their learning goals. Surgical residents’ learning goals include providing continuity throughout a patient’s pre-, peri-, and post-operative care as well as achieving sufficient surgical experience levels in various procedure types and participating in various formal educational activities, among other things. To complicate matters, senior residents often compete with other residents for surgical experience. This paper features experiments using an optimization model and a real dataset. The experiments test the viability of achieving the above goals at a major academic center using existing models of delivering medical education and training to surgical residents. It develops a detailed multi-objective, two-stage stochastic optimization model with anticipatory capabilities solved over a rolling time horizon. A novel feature of the models is the incorporation of learning curve theory in the objection function. Using a deterministic version of the model, we identify bounds on the achievement of learning goals under existing training paradigms. The computational results highlight the structural problems in the current surgical resident educational system. These results further corroborate earlier findings and suggest an educational system redesign is necessary for surgical medical residents. Copyright Springer Science+Business Media New York 2013

Suggested Citation

  • Jonathan Turner & Kibaek Kim & Sanjay Mehrotra & Debra DaRosa & Mark Daskin & Heron Rodriguez, 2013. "Using optimization models to demonstrate the need for structural changes in training programs for surgical medical residents," Health Care Management Science, Springer, vol. 16(3), pages 217-227, September.
  • Handle: RePEc:kap:hcarem:v:16:y:2013:i:3:p:217-227
    DOI: 10.1007/s10729-013-9230-6
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    References listed on IDEAS

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    1. Jeff Linderoth & Alexander Shapiro & Stephen Wright, 2006. "The empirical behavior of sampling methods for stochastic programming," Annals of Operations Research, Springer, vol. 142(1), pages 215-241, February.
    2. Topaloglu, Seyda, 2009. "A shift scheduling model for employees with different seniority levels and an application in healthcare," European Journal of Operational Research, Elsevier, vol. 198(3), pages 943-957, November.
    3. Lori S. Franz & Janis L. Miller, 1993. "Scheduling Medical Residents to Rotations: Solving the Large-Scale Multiperiod Staff Assignment Problem," Operations Research, INFORMS, vol. 41(2), pages 269-279, April.
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    Cited by:

    1. Brech, Claus-Henning & Ernst, Andreas & Kolisch, Rainer, 2019. "Scheduling medical residents’ training at university hospitals," European Journal of Operational Research, Elsevier, vol. 274(1), pages 253-266.
    2. Jonathan P. Turner & Heron E. Rodriguez & Debra A. DaRosa & Mark S. Daskin & Amanda Hayman & Sanjay Mehrotra, 2013. "Northwestern University Feinberg School of Medicine Uses Operations Research Tools to Improve Surgeon Training," Interfaces, INFORMS, vol. 43(4), pages 341-351, August.
    3. Young-Chae Hong & Amy Cohn & Stephen Gorga & Edmond O’Brien & William Pozehl & Jennifer Zank, 2019. "Using Optimization Techniques and Multidisciplinary Collaboration to Solve a Challenging Real-World Residency Scheduling Problem," Interfaces, INFORMS, vol. 49(3), pages 201-212, May.

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