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Mid-term nurse rostering considering cross-training effects

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  • Fügener, Andreas
  • Pahr, Alexander
  • Brunner, Jens O.

Abstract

Hospitals experience challenging times in which both the economic pressure and the challenges of uncertain demand for care increase. One of the most prominent problems in health care operations is the nurse scheduling problem, where nurse rosters are created to cover demand. Cross-training, i.e. educating nurses to work in units other than their dedicated one, offers an opportunity to react to the issues mentioned above within the field of nurse scheduling. We contribute to the nurse cross-training literature in three ways: First, we propose a framework to define and visualize cross-training policies. Second, we introduce a new cross-training policy where each unit trains one dedicated nurse for each other unit. Third, we are the first who develop a mid-term model creating and applying cross-training policies in nurse rostering. Within this new mid-term model, we make use of parameters that allow to control the trade-off between flexibility of nurses and the continuity of care. In two computational studies with 6400 instances we compare our newly developed cross-training policy with three existing policies from the literature, demonstrate the superiority regarding demand coverage and overtime per number of cross-trainings, and compare the effects of cross-training intensity, i.e. the number of cross-trained nurses, with cross-training breadth, i.e. the number of departments a nurse is cross-trained for.

Suggested Citation

  • Fügener, Andreas & Pahr, Alexander & Brunner, Jens O., 2018. "Mid-term nurse rostering considering cross-training effects," International Journal of Production Economics, Elsevier, vol. 196(C), pages 176-187.
  • Handle: RePEc:eee:proeco:v:196:y:2018:i:c:p:176-187
    DOI: 10.1016/j.ijpe.2017.11.020
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    References listed on IDEAS

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    1. Maenhout, Broos & Vanhoucke, Mario, 2013. "An integrated nurse staffing and scheduling analysis for longer-term nursing staff allocation problems," Omega, Elsevier, vol. 41(2), pages 485-499.
    2. William C. Jordan & Stephen C. Graves, 1995. "Principles on the Benefits of Manufacturing Process Flexibility," Management Science, INFORMS, vol. 41(4), pages 577-594, April.
    3. Edieal J. Pinker & Robert A. Shumsky, 2000. "The Efficiency-Quality Trade-Off of Cross-Trained Workers," Manufacturing & Service Operations Management, INFORMS, vol. 2(1), pages 32-48, July.
    4. Gerard M. Campbell, 1999. "Cross-Utilization of Workers Whose Capabilities Differ," Management Science, INFORMS, vol. 45(5), pages 722-732, May.
    5. Dobrzykowski, David & Saboori Deilami, Vafa & Hong, Paul & Kim, Seung-Chul, 2014. "A structured analysis of operations and supply chain management research in healthcare (1982–2011)," International Journal of Production Economics, Elsevier, vol. 147(PB), pages 514-530.
    6. Wright, P. Daniel & Mahar, Stephen, 2013. "Centralized nurse scheduling to simultaneously improve schedule cost and nurse satisfaction," Omega, Elsevier, vol. 41(6), pages 1042-1052.
    7. Paul, Jomon Aliyas & MacDonald, Leo, 2014. "Modeling the benefits of cross-training to address the nursing shortage," International Journal of Production Economics, Elsevier, vol. 150(C), pages 83-95.
    8. Andreas Fügener & Jens O. Brunner & Armin Podtschaske, 2015. "Duty and workstation rostering considering preferences and fairness: a case study at a department of anaesthesiology," International Journal of Production Research, Taylor & Francis Journals, vol. 53(24), pages 7465-7487, December.
    9. Kortbeek, N. & Braaksma, A. & Burger, C.A.J. & Bakker, P.J.M. & Boucherie, R.J., 2015. "Flexible nurse staffing based on hourly bed census predictions," International Journal of Production Economics, Elsevier, vol. 161(C), pages 167-180.
    10. Fügener, Andreas & Hans, Erwin W. & Kolisch, Rainer & Kortbeek, Nikky & Vanberkel, Peter T., 2014. "Master surgery scheduling with consideration of multiple downstream units," European Journal of Operational Research, Elsevier, vol. 239(1), pages 227-236.
    11. Gnanlet, Adelina & Gilland, Wendell G., 2014. "Impact of productivity on cross-training configurations and optimal staffing decisions in hospitals," European Journal of Operational Research, Elsevier, vol. 238(1), pages 254-269.
    12. Stefaan Haspeslagh & Patrick De Causmaecker & Andrea Schaerf & Martin Stølevik, 2014. "The first international nurse rostering competition 2010," Annals of Operations Research, Springer, vol. 218(1), pages 221-236, July.
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    Cited by:

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    2. Kjartan Kastet Klyve & Ilankaikone Senthooran & Mark Wallace, 2023. "Nurse rostering with fatigue modelling," Health Care Management Science, Springer, vol. 26(1), pages 21-45, March.
    3. Schoenfelder, Jan & Bretthauer, Kurt M. & Wright, P. Daniel & Coe, Edwin, 2020. "Nurse scheduling with quick-response methods: Improving hospital performance, nurse workload, and patient experience," European Journal of Operational Research, Elsevier, vol. 283(1), pages 390-403.

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