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Reorganizing the System of Care Surrounding Laparoscopic Surgery: A Cost-Effectiveness Analysis Using Discrete-Event SimulationDepartment 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{at}mgh-ita.org,jstahl@partners.org
Department of Surgery,Massachusetts General Hospital, Harvard Medical School, Cambridge, Massachusetts.
Operating Room Administration, Massachusetts General Hospital, Harvard Medical School, Cambridge, Massachusetts.
Department of Radiology, Massachusetts General Hospital, Harvard Medical School, Cambridge, Massachusetts.
Department of Radiology, Department of Health Policy and Management, Harvard School of Public Health, Cambridge, Massachusetts. 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 systems 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.
Key Words: computer simulation discrete event simulation anesthesia cost-effectiveness
Medical Decision Making, Vol. 24, No. 5,
461-471 (2004) This article has been cited by other articles:
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