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Health economic modeling to support surgery management at a Swedish hospital

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  • Persson, Marie
  • Persson, Jan A.

Abstract

Elective surgery management typically deals with a queue of patients that have to be scheduled for surgery within a certain time frame, considering both medical and economic constraints. In order to prevent the patient queue and waiting times from growing, surgery management has to decide whether to temporarily increase patient throughput at the regional hospital or have some patients scheduled for surgery at another hospital. In Sweden, a newly passed law states that patients who decide to receive surgery should not have to wait more than 90 days before this surgery is carried out. Therefore, if a patient decides to apply the new law by requesting surgery within 90 days, the regional hospital is obliged to arrange and pay for either in-house surgery or surgery at another hospital. In this paper, we suggest an approach using simulation including optimization for modeling surgery management decisions. We study a case based on data from a General Surgery Department at a Swedish hospital and present our results as a health economic evaluation. The results indicate an increase in the mean waiting times for medium prioritized patients when the new law is applied.

Suggested Citation

  • Persson, Marie & Persson, Jan A., 2009. "Health economic modeling to support surgery management at a Swedish hospital," Omega, Elsevier, vol. 37(4), pages 853-863, August.
    • Handle: RePEc:eee:jomega:v:37:y:2009:i:4:p:853-863
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    Cited by:

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    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. 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.
    4. Michael Samudra & Erik Demeulemeester & Brecht Cardoen & Nancy Vansteenkiste & Frank E. Rademakers, 2017. "Due time driven surgery scheduling," Health Care Management Science, Springer, vol. 20(3), pages 326-352, September.
    5. Yiting Xing & Ling Li & Zhuming Bi & Marzena Wilamowska‐Korsak & Li Zhang, 2013. "Operations Research (OR) in Service Industries: A Comprehensive Review," Systems Research and Behavioral Science, Wiley Blackwell, vol. 30(3), pages 300-353, May.
    6. Hejer Khlif Hachicha & Farah Zeghal Mansour, 2018. "Two-MILP models for scheduling elective surgeries within a private healthcare facility," Health Care Management Science, Springer, vol. 21(3), pages 376-392, September.
    7. Pazoki, Mostafa & Samarghandi, Hamed, 2021. "Regulating patient care in walk-in clinics," Omega, Elsevier, vol. 99(C).
    8. Francisco Ballestín & Ángeles Pérez & Sacramento Quintanilla, 2019. "Scheduling and rescheduling elective patients in operating rooms to minimise the percentage of tardy patients," Journal of Scheduling, Springer, vol. 22(1), pages 107-118, February.
    9. Fagerholt, Kjetil & Christiansen, Marielle & Magnus Hvattum, Lars & Johnsen, Trond A.V. & Vabø, Thor J., 2010. "A decision support methodology for strategic planning in maritime transportation," Omega, Elsevier, vol. 38(6), pages 465-474, December.
    10. Rafael L. Patrão & Reinaldo C. Garcia & João M. da Silva, 2022. "An Integrated Two-Level Integer Linear Program (ILP) Model for Elective Surgery Scheduling: A Case Study in an Italian Hospital," Mathematics, MDPI, vol. 10(11), pages 1-18, June.
    11. Francesca Guerriero & Rosita Guido, 2011. "Operational research in the management of the operating theatre: a survey," Health Care Management Science, Springer, vol. 14(1), pages 89-114, March.

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