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“Nursevendor Problem”: Personnel Staffing in the Presence of Endogenous Absenteeism

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  • Linda V. Green

    (Graduate School of Business, Columbia University, New York, New York 10027)

  • Sergei Savin

    (The Wharton School, University of Pennsylvania, Philadelphia, Pennsylvania 19104)

  • Nicos Savva

    (London Business School, London NW1 4SA, United Kingdom)

Abstract

The problem of determining nurse staffing levels in a hospital environment is a complex task because of variable patient census levels and uncertain service capacity caused by nurse absenteeism. In this paper, we combine an empirical investigation of the factors affecting nurse absenteeism rates with an analytical treatment of nurse staffing decisions using a novel variant of the newsvendor model. Using data from the emergency department of a large urban hospital, we find that absenteeism rates are consistent with nurses exhibiting an aversion to higher levels of anticipated workload. Using our empirical findings, we analyze a single-period nurse staffing problem considering both the case of constant absenteeism rate (exogenous absenteeism) as well as an absenteeism rate that is a function of the number of nurses scheduled (endogenous absenteeism). We provide characterizations of the optimal staffing levels in both situations and show that the failure to incorporate absenteeism as an endogenous effect results in understaffing. This paper was accepted by Yossi Aviv, operations management.

Suggested Citation

  • Linda V. Green & Sergei Savin & Nicos Savva, 2013. "“Nursevendor Problem”: Personnel Staffing in the Presence of Endogenous Absenteeism," Management Science, INFORMS, vol. 59(10), pages 2237-2256, October.
    • Handle: RePEc:inm:ormnsc:v:59:y:2013:i:10:p:2237-2256
    DOI: 10.1287/mnsc.2013.1713
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    2. Song-Hee Kim & Carri W. Chan & Marcelo Olivares & Gabriel Escobar, 2015. "ICU Admission Control: An Empirical Study of Capacity Allocation and Its Implication for Patient Outcomes," Management Science, INFORMS, vol. 61(1), pages 19-38, January.
    3. Nasini, Stefano & Nessah, Rabia, 2022. "A multi-machine scheduling solution for homogeneous processing: Asymptotic approximation and applications," International Journal of Production Economics, Elsevier, vol. 251(C).
    4. Susan Feng Lu & Lauren Xiaoyuan Lu, 2017. "Do Mandatory Overtime Laws Improve Quality? Staffing Decisions and Operational Flexibility of Nursing Homes," Management Science, INFORMS, vol. 63(11), pages 3566-3585, November.
    5. Vishal Ahuja & Carlos A. Alvarez & Bradley R. Staats, 2020. "Maintaining Continuity in Service: An Empirical Examination of Primary Care Physicians," Manufacturing & Service Operations Management, INFORMS, vol. 22(5), pages 1088-1106, September.
    6. Kayse Lee Maass & Boying Liu & Mark S. Daskin & Mary Duck & Zhehui Wang & Rama Mwenesi & Hannah Schapiro, 2017. "Incorporating nurse absenteeism into staffing with demand uncertainty," Health Care Management Science, Springer, vol. 20(1), pages 141-155, March.
    7. Gah-Yi Ban & Cynthia Rudin, 2019. "The Big Data Newsvendor: Practical Insights from Machine Learning," Operations Research, INFORMS, vol. 67(1), pages 90-108, January.
    8. David, Guy & Kim, Kunhee Lucy, 2018. "The effect of workforce assignment on performance: Evidence from home health care," Journal of Health Economics, Elsevier, vol. 59(C), pages 26-45.
    9. Irene Lo & Vahideh Manshadi & Scott Rodilitz & Ali Shameli, 2020. "Commitment on Volunteer Crowdsourcing Platforms: Implications for Growth and Engagement," Papers 2005.10731, arXiv.org, revised Jul 2021.
    10. Farbod Farhadi & Sina Ansari & Francisco Jara-Moroni, 2023. "Optimization models for patient and technician scheduling in hemodialysis centers," Health Care Management Science, Springer, vol. 26(3), pages 558-582, September.
    11. Masoud Kamalahmadi & Kurt M. Bretthauer & Jonathan E. Helm & Alex F. Mills & Edwin C. Coe & Alisa Judy-Malcolm & Areeba Kara & Julian Pan, 2023. "Mixing It Up: Operational Impact of Hospitalist Caseload and Case-Mix," Management Science, INFORMS, vol. 69(1), pages 283-307, January.
    12. Eskildsen, Jacob Kjær & Frederiksen, Anders & Løkke, Ann-Kristina, 2018. "Employee Absence: An Organizational Perspective," IZA Discussion Papers 11889, Institute of Labor Economics (IZA).

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