IAD 06-112
Outpatient Waiting Times, Outcomes, and Cost for VA Patients with Diabetes
Steven Daniel Pizer, PhD VA Boston Healthcare System Jamaica Plain Campus, Jamaica Plain, MA Boston, MA Funding Period: September 2007 - September 2010 Portfolio Assignment: Systems Modeling, Design, and Delivery |
BACKGROUND/RATIONALE:
Policymakers have argued that long waits for healthcare will negatively impact health due to delays in diagnosis and treatment. Despite the assumed importance of wait times, little data exists on wait times because the VA is the only United States health care system to systematically collect information on wait times. Therefore, little research has examined the health and cost implications of waiting for health care and this innovative study begins to fill this gap. OBJECTIVE(S): This project will explain the variation within the VA in how long veterans wait for outpatient care with supply and demand characteristics, and examine the potential effects of waiting for outpatient care on health outcomes and health care cost. Using VA administrative data and other publicly available data, we will focus on four objectives: Objective 1: Study and describe the variation in wait times for outpatient care throughout the VA. Objective 2: Develop a statistical model that predicts wait times for outpatient care. Objective 3: Estimate the relationship between waiting for outpatient care, outpatient utilization, and health outcomes for veterans with diabetes. Objective 4: For veterans with diabetes, measure the impact on VA, Medicare, and Medicaid costs of differences in utilization and health outcomes attributable to differences in outpatient wait times. METHODS: This study uses existing administrative data to achieve its objectives. We will estimate statistical models using linked VA, publicly available Medicare and Medicaid data and geographic data. The first model will predict parent station wait times based on demand (e.g. number of veterans in an area) and supply (e.g. number of appointments) characteristics. The next models will examine if veterans with diabetes who visit parent stations with longer wait times are at greater risk for diabetic complications and mortality. The final model will examine the acute and long-term care cost implications of decreasing outpatient wait times. FINDINGS/RESULTS: Models indicate that both supply of appointments and demand for care respond to changes in waiting times. The principal determinant of supply of primary care visits is total available resources, but the evidence suggests that managers respond to changes in waiting times for primary care by shifting resources to and from other services. Compared to supply, demand for primary care appointments appears to be more sensitive to changes in waiting times. Outcome models find longer wait times are significant predictors of stroke for veterans aged 70-74, heart attack for veterans aged 75-79 and for mortality and ACSC hospitalization for veterans aged 80 or older. There is also a significant positive relationship between primary care wait times and hemoglobin A1c levels. IMPACT: Policymakers argue that long waits for healthcare adversely affect health due to delays in diagnosis and treatment. Very little research has examined the implications of waiting for health care because wait times data are not widely available. This study begins to fill the gap by identifying the causes and health effects of long wait times. VA managers should consider providing the chronically ill and elderly populations with priority access to care. External Links for this ProjectDimensions for VADimensions for VA is a web-based tool available to VA staff that enables detailed searches of published research and research projects.Learn more about Dimensions for VA. VA staff not currently on the VA network can access Dimensions by registering for an account using their VA email address. Search Dimensions for this project PUBLICATIONS:Journal Articles
DRA:
Health Systems Science, Diabetes and Other Endocrine Conditions
DRE: Treatment - Comparative Effectiveness Keywords: Cost, Quality assessment, Utilization patterns MeSH Terms: none |