IDEAS home Printed from https://ideas.repec.org/a/eee/soceps/v47y2013i2p131-141.html
   My bibliography  Save this article

Simulating neonatal intensive care capacity in British Columbia

Author

Listed:
  • Fournier, Derrick L.
  • Zaric, Gregory S.

Abstract

Each year, a small number of expectant mothers with high-risk pregnancies in British Columbia (BC) are sent to the United States (US) because of a lack of neonatal intensive care unit (NICU) beds. We developed a discrete-event simulation model to determine the impact of changing the number of NICU beds in BC on the probability of transfer to the US and on overall system costs. The model includes births in 25 different zones at five different levels of care; transitions between levels of care over time; and transfers of patients between zones and to the US when there is insufficient capacity. We parameterized the model using data from the BC Health System, the Canadian Institute for Health Information, published reports, internal hospital data and expert opinion. Our analysis suggests that the province should consider a modest increase in NICU capacity. In particular, the use of a bottleneck approach to identify the type and location of 4 new beds at select hospitals throughout the system resulted in a reduction in the probability of transfer to the US and an increase in annual system costs. A model like the one described in this paper may be useful to evaluate the tradeoffs associated with capacity expansion for a number of different services where Canadians seek care in the US.

Suggested Citation

  • Fournier, Derrick L. & Zaric, Gregory S., 2013. "Simulating neonatal intensive care capacity in British Columbia," Socio-Economic Planning Sciences, Elsevier, vol. 47(2), pages 131-141.
    • Handle: RePEc:eee:soceps:v:47:y:2013:i:2:p:131-141
    DOI: 10.1016/j.seps.2013.01.001
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0038012113000128
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.seps.2013.01.001?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. Reidar Hagtvedt & Paul Griffin & Pınar Keskinocak & Rebecca Roberts, 2009. "A Simulation Model to Compare Strategies for the Reduction of Health-Care--Associated Infections," Interfaces, INFORMS, vol. 39(3), pages 256-270, June.
    2. Lauren Cipriano & Bert Chesworth & Chris Anderson & Gregory Zaric, 2007. "Predicting joint replacement waiting times," Health Care Management Science, Springer, vol. 10(2), pages 195-215, June.
    3. Wang, Qinan, 2004. "Modeling and analysis of high risk patient queues," European Journal of Operational Research, Elsevier, vol. 155(2), pages 502-515, June.
    4. Riitta Marjamaa & Paulus Torkki & Eero Hirvensalo & Olli Kirvelä, 2009. "What is the best workflow for an operating room? A simulation study of five scenarios," Health Care Management Science, Springer, vol. 12(2), pages 142-146, June.
    5. Brailsford, S.C. & Harper, P.R. & Sykes, J., 2012. "Incorporating human behaviour in simulation models of screening for breast cancer," European Journal of Operational Research, Elsevier, vol. 219(3), pages 491-507.
    6. Jacqueline Griffin & Shuangjun Xia & Siyang Peng & Pinar Keskinocak, 2012. "Improving patient flow in an obstetric unit," Health Care Management Science, Springer, vol. 15(1), pages 1-14, March.
    7. Matthew Reynolds & Christos Vasilakis & Monsey McLeod & Nicholas Barber & Ann Mounsey & Sue Newton & Ann Jacklin & Bryony Franklin, 2011. "Using discrete event simulation to design a more efficient hospital pharmacy for outpatients," Health Care Management Science, Springer, vol. 14(3), pages 223-236, September.
    8. Ramwadhdoebe, Sabrina & Buskens, Erik & Sakkers, Ralph J.B. & Stahl, James E., 2009. "A tutorial on discrete-event simulation for health policy design and decision making: Optimizing pediatric ultrasound screening for hip dysplasia as an illustration," Health Policy, Elsevier, vol. 93(2-3), pages 143-150, December.
    9. K Katsaliaki & N Mustafee, 2011. "Applications of simulation within the healthcare context," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 62(8), pages 1431-1451, August.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Kaya, Onur & Teymourifar, Aydin & Ozturk, Gurkan, 2020. "Analysis of different public policies through simulation to increase total social utility in a healthcare system," Socio-Economic Planning Sciences, Elsevier, vol. 70(C).

    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. Jesús Isaac Vázquez-Serrano & Rodrigo E. Peimbert-García & Leopoldo Eduardo Cárdenas-Barrón, 2021. "Discrete-Event Simulation Modeling in Healthcare: A Comprehensive Review," IJERPH, MDPI, vol. 18(22), pages 1-20, November.
    2. Michael Samudra & Carla Van Riet & Erik Demeulemeester & Brecht Cardoen & Nancy Vansteenkiste & Frank E. Rademakers, 2016. "Scheduling operating rooms: achievements, challenges and pitfalls," Journal of Scheduling, Springer, vol. 19(5), pages 493-525, October.
    3. Gouveia, Catarina & Kalakou, Sofia & Cardoso-Grilo, Teresa, 2023. "How to forecast mental healthcare needs? Distinguishing between perceived and unperceived needs and their impact on capacity requirements," Socio-Economic Planning Sciences, Elsevier, vol. 87(PA).
    4. Chong Pan & Dali Zhang & Audrey Kon & Charity Wai & Woo Ang, 2015. "Patient flow improvement for an ophthalmic specialist outpatient clinic with aid of discrete event simulation and design of experiment," Health Care Management Science, Springer, vol. 18(2), pages 137-155, June.
    5. Artur Nagapetyan & Alexander Drozd & Dmitry Subbotovsky, 2023. "How to Determine the Optimal Number of Cardiologists in a Region?," Mathematics, MDPI, vol. 11(21), pages 1-23, October.
    6. 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.
    7. Mielczarek, Bożena, 2014. "Simulation modelling for contracting hospital emergency services at the regional level," European Journal of Operational Research, Elsevier, vol. 235(1), pages 287-299.
    8. Hazel Squires & Michael P. Kelly & Nigel Gilbert & Falko Sniehotta & Robin C. Purshouse, 2023. "The long‐term effectiveness and cost‐effectiveness of public health interventions; how can we model behavior? A review," Health Economics, John Wiley & Sons, Ltd., vol. 32(12), pages 2836-2854, December.
    9. 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.
    10. Navonil Mustafee & Korina Katsaliaki & Paul Fishwick, 2014. "Exploring the modelling and simulation knowledge base through journal co-citation analysis," Scientometrics, Springer;Akadémiai Kiadó, vol. 98(3), pages 2145-2159, March.
    11. Osório, António, 2017. "Self-interest and equity concerns: A behavioural allocation rule for operational problems," European Journal of Operational Research, Elsevier, vol. 261(1), pages 205-213.
    12. Sumi Kim & Seongmoon Kim, 2015. "Differentiated waiting time management according to patient class in an emergency care center using an open Jackson network integrated with pooling and prioritizing," Annals of Operations Research, Springer, vol. 230(1), pages 35-55, July.
    13. Deepa Mishra & Sameer Kumar & Elkafi Hassini, 2019. "Current trends in disaster management simulation modelling research," Annals of Operations Research, Springer, vol. 283(1), pages 1387-1411, December.
    14. Jian-Jun Wang & Zongli Dai & Wenxuan Zhang & Jim Junmin Shi, 2023. "Operating room scheduling for non-operating room anesthesia with emergency uncertainty," Annals of Operations Research, Springer, vol. 321(1), pages 565-588, February.
    15. Mark Roberts & Louise B. Russell & A. David Paltiel & Michael Chambers & Phil McEwan & Murray Krahn, 2012. "Conceptualizing a Model," Medical Decision Making, , vol. 32(5), pages 678-689, September.
    16. Hessam Bavafa & Sergei Savin & Christian Terwiesch, 2021. "Customizing Primary Care Delivery Using E‐Visits," Production and Operations Management, Production and Operations Management Society, vol. 30(11), pages 4306-4327, November.
    17. Mohammadi, M. & Dehbari, S. & Vahdani, Behnam, 2014. "Design of a bi-objective reliable healthcare network with finite capacity queue under service covering uncertainty," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 72(C), pages 15-41.
    18. Julian Schiele & Thomas Koperna & Jens O. Brunner, 2021. "Predicting intensive care unit bed occupancy for integrated operating room scheduling via neural networks," Naval Research Logistics (NRL), John Wiley & Sons, vol. 68(1), pages 65-88, February.
    19. Ivor Langley & Basra Doulla & Hsien-Ho Lin & Kerry Millington & Bertie Squire, 2012. "Modelling the impacts of new diagnostic tools for tuberculosis in developing countries to enhance policy decisions," Health Care Management Science, Springer, vol. 15(3), pages 239-253, September.
    20. Kucukyazici, Beste & Zhang, Yue & Ardestani-Jaafari, Amir & Song, Lijie, 2020. "Incorporating patient preferences in the design and operation of cancer screening facility networks," European Journal of Operational Research, Elsevier, vol. 287(2), pages 616-632.

    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:eee:soceps:v:47:y:2013:i:2:p:131-141. 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: Catherine Liu (email available below). General contact details of provider: http://www.elsevier.com/locate/seps .

    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.