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Spreadsheet Model Helps to Assign Medical Residents at the University of Vermont's College of Medicine

Author

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  • Anton Ovchinnikov

    (Darden Graduate School of Business Administration, University of Virginia, Charlottesville, Virginia 22903)

  • Joseph Milner

    (Joseph L. Rotman School of Management, University of Toronto, Toronto, Ontario, Canada M5S 3E6)

Abstract

This paper describes a spreadsheet model that MBA students enrolled in an MS course constructed to replace the manual method of assigning medical residents in radiology to on-call and emergency rotations at the University of Vermont's College of Medicine. Although it contains more than 10,000 variables, the model was easy to build and solve by practitioners who are “lightly educated” in OR/MS. Based on this group's work, we discuss an approach that end-user practitioners can take to create spreadsheet optimization models. We also provide several observations and argue that spreadsheet models can provide an alternative scheduling method for problems of a smaller scope. Despite the major advances in personnel-scheduling methodologies and software, manual scheduling is still the predominant method used for such smaller-scope problems.

Suggested Citation

  • Anton Ovchinnikov & Joseph Milner, 2008. "Spreadsheet Model Helps to Assign Medical Residents at the University of Vermont's College of Medicine," Interfaces, INFORMS, vol. 38(4), pages 311-323, August.
    • Handle: RePEc:inm:orinte:v:38:y:2008:i:4:p:311-323
    DOI: 10.1287/inte.1070.0337
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    References listed on IDEAS

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    1. Thomas A. Grossman, 2002. "Student Consulting Projects Benefit Faculty and Industry," Interfaces, INFORMS, vol. 32(2), pages 42-48, April.
    2. Berrada, Ilham & Ferland, Jacques A. & Michelon, Philippe, 1996. "A multi-objective approach to nurse scheduling with both hard and soft constraints," Socio-Economic Planning Sciences, Elsevier, vol. 30(3), pages 183-193, September.
    3. Cheang, B. & Li, H. & Lim, A. & Rodrigues, B., 2003. "Nurse rostering problems--a bibliographic survey," European Journal of Operational Research, Elsevier, vol. 151(3), pages 447-460, December.
    4. A.T. Ernst & H. Jiang & M. Krishnamoorthy & B. Owens & D. Sier, 2004. "An Annotated Bibliography of Personnel Scheduling and Rostering," Annals of Operations Research, Springer, vol. 127(1), pages 21-144, March.
    5. Stephen G. Powell, 1997. "The Teachers' Forum: From Intelligent Consumer to Active Modeler, Two MBA Success Stories," Interfaces, INFORMS, vol. 27(3), pages 88-98, June.
    6. Dmitry Krass & Anton Ovchinnikov, 2006. "The University of Toronto’s Rotman School of Management Uses Management Science to Create MBA Study Groups," Interfaces, INFORMS, vol. 36(2), pages 126-137, April.
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    Citations

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    Cited by:

    1. Jens Brunner & Günther Edenharter, 2011. "Long term staff scheduling of physicians with different experience levels in hospitals using column generation," Health Care Management Science, Springer, vol. 14(2), pages 189-202, June.
    2. Manion Anderson & Merve Bodur & Scott Rathwell & Vahid Sarhangian, 2023. "Optimization Helps Scheduling Nursing Staff at the Long-Term Care Homes of the City of Toronto," Interfaces, INFORMS, vol. 53(2), pages 133-154, March.
    3. 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.
    4. Frederick M Howard & Catherine A Gao & Christopher Sankey, 2020. "Implementation of an automated scheduling tool improves schedule quality and resident satisfaction," PLOS ONE, Public Library of Science, vol. 15(8), pages 1-9, August.
    5. Jan Schoenfelder & Christian Pfefferlen, 2018. "Decision Support for the Physician Scheduling Process at a German Hospital," Service Science, INFORMS, vol. 10(3), pages 215-229, September.
    6. Van den Bergh, Jorne & Beliën, Jeroen & De Bruecker, Philippe & Demeulemeester, Erik & De Boeck, Liesje, 2013. "Personnel scheduling: A literature review," European Journal of Operational Research, Elsevier, vol. 226(3), pages 367-385.
    7. Hannah K. Smalley & Pınar Keskinocak & Atul Vats, 2015. "Physician Scheduling for Continuity: An Application in Pediatric Intensive Care," Interfaces, INFORMS, vol. 45(2), pages 133-148, April.
    8. Erhard, Melanie & Schoenfelder, Jan & Fügener, Andreas & Brunner, Jens O., 2018. "State of the art in physician scheduling," European Journal of Operational Research, Elsevier, vol. 265(1), pages 1-18.
    9. Castaño, Fabián & Velasco, Nubia, 2020. "Exact and heuristic approaches for the automated design of medical trainees rotation schedules," Omega, Elsevier, vol. 97(C).
    10. Sanjay L. Ahire, 2023. "McLeod Health Optimizes Staffing for Patient Room Cleaning," Interfaces, INFORMS, vol. 53(2), pages 155-168, March.

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