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Assigning patients to nurses in neonatal intensive care

Author

Listed:
  • C Mullinax

    (PricewaterhouseCoopers)

  • M Lawley

    (Purdue University)

Abstract

An intensive care nursery provides health care for critically ill newborn infants. During a typical shift, infants range from those needing only occasional care to those requiring constant attention. At the beginning of each shift, the head nurse groups the patients for assignment to staff nurses. Typically each nurse cares for one group of infants throughout the shift. The large variation in infant conditions along with several complicating side constraints makes it difficult to develop balanced nurse work loads. We develop a mathematical programming approach for achieving better workload balance. We first develop a detailed neonatal acuity system that quantifies the nursing workload of each patient. We then develop an integer linear program that assigns patients to nurses while balancing nurse workloads. Because this model is computationally intractable, we develop a heuristic that exploits the fact that most nurseries are divided into a number of physical zones. We use ten case studies taken from a major university hospital to benchmark the performance of this heuristic. We also perform a designed experiment using randomly generated problems that examines the effect of nursery parameters on heuristic performance.

Suggested Citation

  • C Mullinax & M Lawley, 2002. "Assigning patients to nurses in neonatal intensive care," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 53(1), pages 25-35, January.
    • Handle: RePEc:pal:jorsoc:v:53:y:2002:i:1:d:10.1057_palgrave.jors.2601265
    DOI: 10.1057/palgrave.jors.2601265
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    Citations

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    Cited by:

    1. Durai Sundaramoorthi & Victoria Chen & Jay Rosenberger & Seoung Kim & Deborah Buckley-Behan, 2009. "A data-integrated simulation model to evaluate nurse–patient assignments," Health Care Management Science, Springer, vol. 12(3), pages 252-268, September.
    2. Belií«n, Jeroen & Demeulemeester, Erik, 2008. "A branch-and-price approach for integrating nurse and surgery scheduling," European Journal of Operational Research, Elsevier, vol. 189(3), pages 652-668, September.
    3. A Hertz & N Lahrichi, 2009. "A patient assignment algorithm for home care services," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 60(4), pages 481-495, April.
    4. Gilles Pesant, 2015. "Achieving Domain Consistency and Counting Solutions for Dispersion Constraints," INFORMS Journal on Computing, INFORMS, vol. 27(4), pages 690-703, November.
    5. Jie Bai & Andreas Fügener & Jan Schoenfelder & Jens O. Brunner, 2018. "Operations research in intensive care unit management: a literature review," Health Care Management Science, Springer, vol. 21(1), pages 1-24, March.
    6. Johannes Vass & Marie-Louise Lackner & Christoph Mrkvicka & Nysret Musliu & Felix Winter, 2022. "Exact and meta-heuristic approaches for the production leveling problem," Journal of Scheduling, Springer, vol. 25(3), pages 339-370, June.
    7. Philippe Olivier & Andrea Lodi & Gilles Pesant, 2021. "The Quadratic Multiknapsack Problem with Conflicts and Balance Constraints," INFORMS Journal on Computing, INFORMS, vol. 33(3), pages 949-962, July.
    8. 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.
    9. Salem Al-Yakoob & Hanif Sherali & Mona Al-Jazzaf, 2010. "A mixed-integer mathematical modeling approach to exam timetabling," Computational Management Science, Springer, vol. 7(1), pages 19-46, January.
    10. Duraikannan Sundaramoorthi & Victoria Chen & Jay Rosenberger & Seoung Kim & Deborah Buckley-Behan, 2010. "A data-integrated simulation-based optimization for assigning nurses to patient admissions," Health Care Management Science, Springer, vol. 13(3), pages 210-221, September.
    11. Philippe Olivier & Andrea Lodi & Gilles Pesant, 2022. "Measures of balance in combinatorial optimization," 4OR, Springer, vol. 20(3), pages 391-415, September.

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