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Reorganizing the System of Care Surrounding Laparoscopic Surgery: A Cost-Effectiveness Analysis Using Discrete-Event Simulation

Author

Listed:
  • James E. Stahl

    (Department of Radiology, Department of Medicine, Massachusetts General Hospital, Harvard Medical School, Cambridge, Massachusetts; Institute for Technology Assessment, Massachusetts General Hospital, 101 Merimac St., 10th floor, Boston, MA 02114; phone: 617-724-4447; fax: 617-726-9414james@mgh-ita.org , jstahl@partners.org.)

  • David Rattner

    (Department of Surgery,Massachusetts General Hospital, Harvard Medical School, Cambridge, Massachusetts.)

  • Richard Wiklund

    (Operating Room Administration, Massachusetts General Hospital, Harvard Medical School, Cambridge, Massachusetts.)

  • Jessica Lester
  • Molly Beinfeld

    (Department of Radiology, Massachusetts General Hospital, Harvard Medical School, Cambridge, Massachusetts.)

  • G. Scott Gazelle

    (Department of Radiology, Department of Health Policy and Management, Harvard School of Public Health, Cambridge, Massachusetts.)

Abstract

Purpose. To determine the cost-effectiveness of a proposed reorganization of surgical and anesthesia care to balance patient volume and safety. Methods . Discrete-event simulation methods were used to compare current surgical practice with a newmodular system in which patient care is handed off between 2 anesthesiologists. Ahealth care system’s perspective, using hospital and professional costs, was chosen for the cost-effectiveness analysis. Outcomes were patient throughput, flow time, wait time, and resource use. Sensitivity analyses were performed on staffing levels, mortality rates, process times, and scheduled patient volume . Results . The new strategy was more effective (average 4.41 patients/d [median = 5] v. 4.29 [median = 4]) and had similar costs (average cost/ patient/d = $5327 v. $5289) to the current strategywith an incremental cost-effectiveness of $318/additional patient treated/d. Surgical mortality rate must be >4% or hand-off delay >15min before the new strategy is no longermore effective . Conclusion .The proposed system is more cost-effective relative to current practice over a wide range of mortality rates, hand-off times, and scheduled patient volumes.

Suggested Citation

  • James E. Stahl & David Rattner & Richard Wiklund & Jessica Lester & Molly Beinfeld & G. Scott Gazelle, 2004. "Reorganizing the System of Care Surrounding Laparoscopic Surgery: A Cost-Effectiveness Analysis Using Discrete-Event Simulation," Medical Decision Making, , vol. 24(5), pages 461-471, October.
  • Handle: RePEc:sae:medema:v:24:y:2004:i:5:p:461-471
    DOI: 10.1177/0272989X04268951
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    Cited by:

    1. Stefanini, Alessandro & Aloini, Davide & Benevento, Elisabetta & Dulmin, Riccardo & Mininno, Valeria, 2020. "A data-driven methodology for supporting resource planning of health services," Socio-Economic Planning Sciences, Elsevier, vol. 70(C).
    2. Michael Thorwarth & Wael Rashwan & Amr Arisha, 2016. "An analytical representation of flexible resource allocation in hospitals," Flexible Services and Manufacturing Journal, Springer, vol. 28(1), pages 148-165, June.
    3. Eren Demir & David Southern, 2017. "Enabling better management of patients: discrete event simulation combined with the STAR approach," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 68(5), pages 577-590, May.
    4. Thomas Rohleder & Diane Bischak & Leland Baskin, 2007. "Modeling patient service centers with simulation and system dynamics," Health Care Management Science, Springer, vol. 10(1), pages 1-12, February.
    5. Abo-Hamad, Waleed & Arisha, Amr, 2013. "Simulation-based framework to improve patient experience in an emergency department," European Journal of Operational Research, Elsevier, vol. 224(1), pages 154-166.
    6. 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.
    7. Reda Lebcir & Usame Yakutcan & Eren Demir, 2022. "A decision support tool with health economic modelling for better management of DVT patients," Health Economics Review, Springer, vol. 12(1), pages 1-16, December.
    8. Boris Sobolev & David Harel & Christos Vasilakis & Adrian Levy, 2008. "Using the Statecharts paradigm for simulation of patient flow in surgical care," Health Care Management Science, Springer, vol. 11(1), pages 79-86, March.

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