Community health centers (CHCs) play an essential role in the U.S. health care system by delivering primary care to a medically underserved population of approximately 26 million individuals in more than 1,300 CHCs regardless of patients' ability to pay. Given this mission, CHCs historically have been exposed to relatively high financial risk. Federal funding for CHCs increased substantially through a trust fund established under the Affordable Care Act; however, trust funding currently is scheduled to end in 2019. The financial outlook for CHCs is threatened further as Congress considers options to significantly reduce funding for Medicaid expansion and Marketplace subsidies. CHC viability depends upon sustainable financial health. To date, studies of the ACA impact on CHC financial performance have focused on the effects of changing sources of revenue. Yet financial margins are comprised of both revenue and cost components. This project is unique in taking a supply side approach to CHC performance by estimating economic cost functions premised on the microeconomic theory of the firm. In health care, cost function analyses have been used primarily in analyses in the hospital and nursing home literatures. Our project is the first study to apply these methods to CHCs. We propose to employ a unique and underutilized panel database to explore CHC costs and to identify drivers of CHC cost efficiency as they relate to current policy challenges facing CHCs. We initially will provide a detailed description of national level variation in various components of CHC costs, establishing baseline estimates for policy-meaningful groupings such as Medicaid-expansion versus non-expansion states and high versus low medical shortage areas, and trends in the 2011-2018 study period. Next we will construct key variables unique to CHCs that will serve as building blocks for CHC cost function estimation. These include a wage index (labor input price), a cost of capital measure, a facility case-mix index, and composite quality scores. Using these measures, we will estimate multi-product translog cost functions in our main empirical specification, and estimate semi-log models in sensitivity analyses. We will apply the results of our cost function estimations to produce a set of constructs useful in addressing policy-relevant issues. First, we will assess whether CHCs experience cost-savings from service expansion versus contraction. Second we will examine potential cost savings and complementarities from integrating primary care visits and more specialized services in centers, notably mental health. Third, as funding constraints may affect quality of care, we will explore the potential trade-off between CHC costs and quality of care.
Community health centers (CHCs) play an essential role in the U.S. health care system by delivering primary care to a medically underserved population of approximately 26 million individuals. Given this mission, CHCs historically have been exposed to relatively high financial risk. By applying economic principles to a uniquely constructed database, this project will identify drivers of CHC cost efficiency as they relate to current policy challenges facing CHCs.
