Vogel B, Syam MS, Cowper D, Stephens G, Bates B; Academy for Health Services Research and Health Policy. Meeting.
Abstr Acad Health Serv Res Health Policy Meet. 2002; 19: 45.
University of Florida, Box 100177 Health Science Center, Gainesville, FL 32653; Tel: (352) 265-8035; Fax: (352) 265-8047; E-mail: bvogel@hpe.ufl.edu
RESEARCH OBJECTIVE: The objective of this research is to demonstrate a prototype mathematical optimization model for locating traumatic brain injury treatment units geographically. The goal of the model is to allocate a limited number of TBI treatment units to existing VA medical centers so as to minimize the sum of patient travel costs and VA treatment costs while ensuring service for those veterans diagnosed with TBI in Veterans Integrated Service Network 8, Florida, Puerto Rico, and South Georgia. Through developing a prototype for VISN 8, we demonstrate both the capabilities of the model and the feasibility of constructing such a model for the entire VA system. STUDY DESIGN: We present a mixed integer programming model where the objective function to be minimized is the sum of patient travel costs and VA patient treatment costs. The constraints in this model represent the geographical origins of VA TBI patients. Patients' zip codes of residence from the VA's Patient Treatment File comprise a key data element for this model. Combined with the zip codes of VA treatment sites, we estimated the travel distances for VA TBI inpatients in VISN 8 over the past three years. We calculated approximate travel costs based on these travel distances and combined them with estimates of the VA costs of providing care to these patients from the VA Health Economics Resource Center's Average Cost Dataset to parameterize the objective function. We solved this optimization model under varying configurations to demonstrate both how the model operates and how optimal geographic locations vary as model parameters and constraints are changed. POPULATION STUDIED: Veterans seen in VISN 8 with a primary or secondary diagnosis of traumatic brain injury during 1998-2000. PRINCIPAL FINDINGS: We demonstrate how the optimal number of TBI units varies with changes in travel, production costs, and patient volume and location. We also exercise the model to present estimates of the expected costs of closure of a TBI unit and their attendant incidence. Such exercises can be extremely useful in informing policymakers about the often otherwise hidden costs of resource allocation decisions. CONCLUSIONS: Our prototype model demonstrates both the usefulness of a more sophisticated analytical approach to planning decisions as well as the feasibility of constructing such a model for the VA nationwide. We believe that our work demonstrates a powerful new method for informing and supporting important resource allocation decisions within VA rehabilitation. IMPLICATIONS FOR POLICY, DELIVERY OR PRACTICE: Capacity planning within the VA is inherently a political process. VA resources are important, highly visible public projects with considerable payoffs to the elected officials who manage to attract them. At the same time, management science and economics offer powerful tools to inform policymakers about the explicit and implicit costs of their decisions. While such tools will never entirely replace political considerations in the allocation of VA resources, they can and should provide insight into the consequences of alternative allocations of resources. PRIMARY FUNDING SOURCE: VA
Publication Types:
Keywords:
- Costs and Cost Analysis
- Economics, Medical
- Florida
- Health Care Costs
- Health Resources
- Health Services Accessibility
- Health Services Research
- Hospitals, Veterans
- Humans
- Insurance, Health
- Puerto Rico
- Research
- Research Design
- Veterans
- economics
- surgery
- therapy
- hsrmtgs
Other ID:
UI: 102274139
From Meeting Abstracts