IDEAS home Printed from https://ideas.repec.org/a/kap/hcarem/v28y2025i1d10.1007_s10729-025-09697-8.html
   My bibliography  Save this article

Inter-organizational pooling of NICU nurses in the Dutch neonatal network: a simulation-optimization study

Author

Listed:
  • Gréanne Leeftink

    (University of Twente)

  • Kimberley Morris

    (University of Twente)

  • Tim Antonius

    (Department of Pediatrics - Division of Neonatology Radboud UMC Amalia Children’s Hospital)

  • Willem de Vries

    (UMC Utrecht
    Amsterdam UMC)

  • Erwin Hans

    (University of Twente)

Abstract

Neonatology care, the care for premature and severely ill babies, is increasingly confronted with capacity challenges. The entire perinatal care chain, including the Neonatal Intensive Care Unit (NICU), operates at high occupation levels. This results in refusals, leading to undesirable transports to other centers or even abroad, which affects quality of care, length of stay, and safety of these babies, and places a heavy burden on patients, their families, and involved caregivers. In this work we assess the improvement potential of network collaboration strategies that focus on reducing the number of patient transports, by allowing flexible deployment of nurses over the existing NICUs to match short-term changes in patient demand. We develop a discrete event simulation with an integrated optimization module for shift allocation and transfer optimization. A case study for the Dutch national NICU network, involving 9 NICU locations and current transport of 15% of all NICU patients in case of no flexible deployment, shows the potential of transporting staff instead of patients: About 70% of patient transports can be eliminated in case of 15-50% capacity sharing, and about 35% of nationwide transports is eliminated with up to 15% capacity sharing in the Dutch’s main conurbation area only.

Suggested Citation

  • Gréanne Leeftink & Kimberley Morris & Tim Antonius & Willem de Vries & Erwin Hans, 2025. "Inter-organizational pooling of NICU nurses in the Dutch neonatal network: a simulation-optimization study," Health Care Management Science, Springer, vol. 28(1), pages 64-83, March.
  • Handle: RePEc:kap:hcarem:v:28:y:2025:i:1:d:10.1007_s10729-025-09697-8
    DOI: 10.1007/s10729-025-09697-8
    as

    Download full text from publisher

    File URL: http://link.springer.com/10.1007/s10729-025-09697-8
    File Function: Abstract
    Download Restriction: Access to the full text of the articles in this series is restricted.

    File URL: https://libkey.io/10.1007/s10729-025-09697-8?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Carina Fagefors & Björn Lantz & Peter Rosén, 2020. "Creating Short-Term Volume Flexibility in Healthcare Capacity Management," IJERPH, MDPI, vol. 17(22), pages 1-18, November.
    2. Md Asaduzzaman & Thierry Chaussalet & Nicola Robertson, 2010. "A loss network model with overflow for capacity planning of a neonatal unit," Annals of Operations Research, Springer, vol. 178(1), pages 67-76, July.
    3. 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.
    4. Jang, Hoon & Lee, Jun-Ho, 2019. "A hierarchical location model for determining capacities of neonatal intensive care units in Korea," Socio-Economic Planning Sciences, Elsevier, vol. 68(C).
    5. Ali Kokangul & Serap Akcan & Mufide Narli, 2017. "Optimizing nurse capacity in a teaching hospital neonatal intensive care unit," Health Care Management Science, Springer, vol. 20(2), pages 276-285, June.
    6. Jang, Hoon & Hwang, Kyosang & Lee, Taeho & Lee, Taesik, 2019. "Designing robust rollout plan for better rural perinatal care system in Korea," European Journal of Operational Research, Elsevier, vol. 274(2), pages 730-742.
    7. Shola Adeyemi & Thierry Chaussalet & Eren Demir, 2011. "Nonproportional random effects modelling of a neonatal unit operational patient pathways," Statistical Methods & Applications, Springer;Società Italiana di Statistica, vol. 20(4), pages 507-518, November.
    8. Asaduzzaman, Md & Chaussalet, Thierry J., 2014. "Capacity planning of a perinatal network with generalised loss network model with overflow," European Journal of Operational Research, Elsevier, vol. 232(1), pages 178-185.
    9. 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.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Yuta Kanai & Hideaki Takagi, 2021. "Markov chain analysis for the neonatal inpatient flow in a hospital," Health Care Management Science, Springer, vol. 24(1), pages 92-116, March.
    2. Yanting Chen & Jingui Xie & Taozeng Zhu, 2023. "Overflow in systems with two servers: the negative consequences," Flexible Services and Manufacturing Journal, Springer, vol. 35(3), pages 838-863, September.
    3. 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.
    4. Steffen Heider & Jan Schoenfelder & Thomas Koperna & Jens O. Brunner, 2022. "Balancing control and autonomy in master surgery scheduling: Benefits of ICU quotas for recovery units," Health Care Management Science, Springer, vol. 25(2), pages 311-332, June.
    5. Hideaki Takagi & Yuta Kanai & Kazuo Misue, 2017. "Queueing network model for obstetric patient flow in a hospital," Health Care Management Science, Springer, vol. 20(3), pages 433-451, September.
    6. Asaduzzaman, Md & Chaussalet, Thierry J., 2014. "Capacity planning of a perinatal network with generalised loss network model with overflow," European Journal of Operational Research, Elsevier, vol. 232(1), pages 178-185.
    7. 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.
    8. Adrien Wartelle & Farah Mourad-Chehade & Farouk Yalaoui & David Laplanche & Stéphane Sanchez, 2024. "Changing the perspective of system crowding evaluation using a new congestion measure: application to the Emergency Department," Operational Research, Springer, vol. 24(4), pages 1-35, December.
    9. Andrés Miniguano-Trujillo & Fernanda Salazar & Ramiro Torres & Patricio Arias & Koraima Sotomayor, 2021. "An integer programming model to assign patients based on mental health impact for tele-psychotherapy intervention during the Covid–19 emergency," Health Care Management Science, Springer, vol. 24(2), pages 286-304, June.
    10. David D. Cho & Kurt M. Bretthauer & Jan Schoenfelder, 2023. "Patient-to-nurse ratios: Balancing quality, nurse turnover, and cost," Health Care Management Science, Springer, vol. 26(4), pages 807-826, December.
    11. Samantha L. Zimmerman & Alexander R. Rutherford & Alexa Waall & Monica Norena & Peter Dodek, 2023. "A queuing model for ventilator capacity management during the COVID-19 pandemic," Health Care Management Science, Springer, vol. 26(2), pages 200-216, June.
    12. Song-Hee Kim & Ward Whitt, 2014. "Are Call Center and Hospital Arrivals Well Modeled by Nonhomogeneous Poisson Processes?," Manufacturing & Service Operations Management, INFORMS, vol. 16(3), pages 464-480, July.
    13. De Vuyst, Stijn & Bruneel, Herwig & Fiems, Dieter, 2014. "Computationally efficient evaluation of appointment schedules in health care," European Journal of Operational Research, Elsevier, vol. 237(3), pages 1142-1154.
    14. Nico Dijk & Barteld Schilstra, 2022. "On two product form modifications for finite overflow systems," Annals of Operations Research, Springer, vol. 310(2), pages 519-549, March.
    15. Hayford Asare Obeng & Richard Arhinful & Dagnu Haile Tessema & Japheth Ahmed Nuhu, 2025. "The mediating role of organisational stress in the relationship between gender diversity and employee performance in Ghanaian public hospitals," Future Business Journal, Springer, vol. 11(1), pages 1-19, December.
    16. Shola Adeyemi & Eren Demir, 2020. "Modelling the neonatal system: A joint analysis of length of stay and patient pathways," International Journal of Health Planning and Management, Wiley Blackwell, vol. 35(3), pages 704-717, May.
    17. Josephine Varney & Nigel Bean & Mark Mackay, 2019. "The self-regulating nature of occupancy in ICUs: stochastic homoeostasis," Health Care Management Science, Springer, vol. 22(4), pages 615-634, December.
    18. Elvan Gökalp & Nalan Gülpınar & Xuan Vinh Doan, 2020. "Capacity Planning for Networks of Stem‐Cell Donation Centers under Uncertainty," Production and Operations Management, Production and Operations Management Society, vol. 29(2), pages 281-297, February.
    19. Sean Harris & Ronald Mcgarvey & Andreas Thorsen & Maggie Thorsen, 2024. "Inferred attractiveness gravity-based models for estimating realized access at rural hospitals," Post-Print hal-04836421, HAL.
    20. Kyosang Hwang & Tooba Binte Asif & Taesik Lee, 2022. "Choice-driven location-allocation model for healthcare facility location problem," Flexible Services and Manufacturing Journal, Springer, vol. 34(4), pages 1040-1065, December.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:kap:hcarem:v:28:y:2025:i:1:d:10.1007_s10729-025-09697-8. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Sonal Shukla or Springer Nature Abstracting and Indexing (email available below). General contact details of provider: http://www.springer.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.