Since 1965, Community Health Centers (CHCs) have delivered primary and preventive health care at free or reduced cost to disadvantaged and uninsured Americans (Hawkins and Schwartz 2003). Although political support for CHCs has varied over time, both Republicans and Democrats have recently championed their expansion. Between 2001 and 2007, the Federal Health Center Growth Initiative doubled CHC funding from $1 to $2 billion (US DHHS 2008). More recently, the Patient Protection and Affordable Care Act (PPACA) appropriates $11 billion to CHCs over five years in addition to $9.5 billion in annual discretionary funding with the goal of doubling the annual CHC patient population to 40 million by 2015.
Many studies provide highly suggestive evidence that CHCs increase health care access, improve health, and reduce health disparities, but a lack of data and reliance on cross-sectional methodology limits these studies? relevance for public policy. The broad goal of this project are to provide the best available evidence of the impact of CHCs on health care utilization and health outcomes from 1965 to the present and to use this knowledge to inform their expansion under the PPACA.
Specifically, we will (1) compile and digitize a comprehensive database on CHC availability and funding from 1965 to 2005 and release them for use by other researchers; (2) link this database to a variety of publically available databases and, for the 1974 to present period, link these data to a newly created ?Index of Medical Underservice? (IMU)?the basis of CHC funding today; (3) test the assumptions of alternative quasi-experimental methodologies for evaluating the causal impact of CHCs on health outcomes; and (4) quantify (based upon analysis in 3) across the age distribution and by race the impact of CHCs on use of health care, health outcomes, mortality, and other human capital investments.
This project will contribute to social science knowledge and public policy by providing new data for research on CHCs, producing a comprehensive analysis of the relationship between IMU rating and alternative measures of medical underservice (a topic important to current policy), developing and testing new methodologies for causal inference with observational data, and generating new, internally-valid estimates of the effects of investments in public health infrastructure on the health of Americans.
