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Identifying Good Nursing Levels: A Queuing Approach

Author

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  • Natalia Yankovic

    (Columbia Business School, New York, New York 10025)

  • Linda V. Green

    (Columbia Business School, New York, New York 10025)

Abstract

Nursing care is arguably the single biggest factor in both the cost of hospital care and patient satisfaction. Inadequate inpatient nursing levels have also been cited as a significant factor in medical errors and emergency room overcrowding. Yet, there is widespread dissatisfaction with the current methods of determining nurse staffing levels, including the most common one of using minimum nurse-to-patient ratios. In this paper, we represent the nursing system as a variable finite-source queuing model. We develop a reliable, tractable, easily parameterized two-dimensional model to approximate the actual interdependent dynamics of bed occupancy levels and demands for nursing. We use this model to show how unit size, nursing intensity, occupancy levels, and unit length-of-stay affect the impact of nursing levels on performance and thus how inflexible nurse-to-patient ratios can lead to either understaffing or overstaffing. The model is also useful for estimating the impact of nurse staffing levels on emergency department overcrowding.

Suggested Citation

  • Natalia Yankovic & Linda V. Green, 2011. "Identifying Good Nursing Levels: A Queuing Approach," Operations Research, INFORMS, vol. 59(4), pages 942-955, August.
    • Handle: RePEc:inm:oropre:v:59:y:2011:i:4:p:942-955
    DOI: 10.1287/opre.1110.0943
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    References listed on IDEAS

    as
    1. Linda Green, 2006. "Queueing Analysis in Healthcare," International Series in Operations Research & Management Science, in: Randolph W. Hall (ed.), Patient Flow: Reducing Delay in Healthcare Delivery, chapter 0, pages 281-307, Springer.
    2. Lapierre, Sophie D. & Goldsman, David & Cochran, Roger & DuBow, Janice, 1999. "Bed allocation techniques based on census data," Socio-Economic Planning Sciences, Elsevier, vol. 33(1), pages 25-38, March.
    3. Holmes E. Miller & William P. Pierskalla & Gustave J. Rath, 1976. "Nurse Scheduling Using Mathematical Programming," Operations Research, INFORMS, vol. 24(5), pages 857-870, October.
    4. Jaumard, Brigitte & Semet, Frederic & Vovor, Tsevi, 1998. "A generalized linear programming model for nurse scheduling," European Journal of Operational Research, Elsevier, vol. 107(1), pages 1-18, May.
    5. Edward P. C. Kao, 1974. "Modeling the Movement of Coronary Patients within a Hospital by Semi-Markov Processes," Operations Research, INFORMS, vol. 22(4), pages 683-699, August.
    6. Linda V. Green & Peter J. Kolesar, 2004. "ANNIVERSARY ARTICLE: Improving Emergency Responsiveness with Management Science," Management Science, INFORMS, vol. 50(8), pages 1001-1014, August.
    7. John C. Hershey & Elliott N. Weiss & Morris A. Cohen, 1981. "A Stochastic Service Network Model with Application to Hospital Facilities," Operations Research, INFORMS, vol. 29(1), pages 1-22, February.
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