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Prentice J, Pizer SD. Are VA Health Care Services rationed? Using VA Wait Times to Model Supply and Demand for VA Services. Poster session presented at: AcademyHealth Annual Research Meeting; 2009 Jun 28; Chicago, IL.
Research Objective: The Department of Veterans Affairs (VA) reconciles the imbalance between supply and demand for healthcare through wait times. In effect, waiting for care is the price veterans pay for using the VA health care system. Over the last decade, the VA has invested significant resources into decreasing wait times for appointments through performance measures and the Advanced Clinic Access Initiative. These initiatives focus on developing a more efficient scheduling environment, which increases facilities' capacity to provide appointments and decreases waits. However, policies aimed at decreasing wait times have not considered how demand for VA care changes as wait times change (e.g. price elasticity of demand). This research is the first to use wait times to model the price elasticity of supply and demand for VA services. Study Design: This is a cross-sectional study that models supply and demand for primary care separately. Supply in a particular month is defined as the total number of primary care appointments scheduled to occur in that month. The main predictors of supply are the average wait times for new patients for primary care in the previous month, VA medical center budget and the number of community based outpatient clinics a VA medical center has. Demand in a particular month is defined as the estimated number of primary care appointments that were entered into the schedule in that month, regardless of when they were scheduled to occur. The main predictors of demand are predicted primary care wait time for new patients, population need characteristics (e.g. number of veterans in the area, per capita income), and the availability of non-VA options in the area (e.g. Medicare HMOs). Due to the endogenous relationship between wait times and demand, we instrument for current primary care wait times using lagged wait times. Population Studied: All VA medical centers providing outpatient primary care services between 2002 and 2005. Principal Findings: There is a large and significant negative relationship between predicted wait times and the estimated number of appointments demanded. In contrast, there is a small significant relationship between higher wait times in the previous month and a greater number of appointments supplied in the current month. Conclusions: VA facilities are responsive to wait times as the number of scheduled appointments increases when wait times increase in the previous month. However, VA patients are even more sensitive to wait times, exiting the VA system as wait times increase and reducing the demand for VA services. Impact Statements: Substantial progress has been made in reducing VA wait times by focusing on how to increase capacity through changes in scheduling. However, policymakers have not considered how decreases in wait times will influence demand for VA services. This research indicates many veterans adjust their demand for VA services in response to changes in waiting times. Consequently, resources committed to expanding capacity will have part of their effect on waiting times offset by the demand response.
