Responding to traveling patients' seasonal demands for health care services in the Veterans Health Administration
Massachusetts Institute of Technology. Engineering Systems Division.
Deborah Nightingale and Mehmet Erkan Ceyhan.
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The Veterans Health Administration (VHA) provides care to over eight million Veterans and operates over 1,700 sites of care distributed across twenty-one regional networks in the United States. Health care providers within VHA report large seasonal variation in the demand for services, especially in healthcare systems located in the southern U.S. that experience a large influx of "snowbirds" during the winter. Since the majority of resource allocation activities are carried out through a single annual budgeting process at the start of the fiscal year, the seasonal load imposed by "traveling Veterans," defined as Veterans that seek care at VHA sites outside of their home network, make providing high quality services more difficult. This work constitutes the first major effort within VHA to understand the impact of traveling Veterans. We found a significant traveling Veteran population (6.6% of the total number of appointments), distributed disproportionately across the VHA networks. Strong seasonal fluctuations in demand were also discovered, particularly for the VA Bay Pines Healthcare System, in Bay Pines, Florida. Our analysis further indicated that traveling Veterans imposed a large seasonal load (up to 46%) on the Module A clinic at Bay Pines. We developed seasonal autoregressive integrated moving average (SARIMA) models to help the clinic better forecast demand for its services by traveling Veterans. Our models were able to project demand, in terms of encounters and unique patients, with significantly less error than the traditional historical average methods. The SARIMA model for uniques was then used in a Monte Carlo simulation to understand how clinic resources are utilized over time. The simulation revealed that physicians at Module A are over-utilized, ranging from a minimum of 92.6% (June 2013) to maximum 207.4% (January 2013). These results evince the need to reevaluate how the clinic is currently staffed. More broadly, this research presents an example of how simple operations management methods can be deployed to aid operational decision-making at other clinics, facilities, and medical centers both within and outside VHA.
Thesis (S.M. in Technology and Policy)--Massachusetts Institute of Technology, Engineering Systems Division, 2013.Cataloged from PDF version of thesis.Includes bibliographical references (p. 60-62).
DepartmentMassachusetts Institute of Technology. Engineering Systems Division.; Massachusetts Institute of Technology. Engineering Systems Division
Massachusetts Institute of Technology
Engineering Systems Division.