Health Information Technology (HIT) has been recommended as a means to lower health care costs, improve quality, and promote patient safety. One element of Health Information Technology that has helped improve quality of care is clinical decision support systems (CDSS). The proposed dissertation research will investigate the degree to which increased use of CDSS may contribute to reducing racial and rural/urban health quality disparities. Differences in process and outcome quality indicators will be studied by examining acute myocardial infarction (AMI) and pneumonia patients within hospitals with and without CDSS. Black and Hispanic patients have been shown to receive lower recommended care for these two conditions, and as a result suffer poorer health outcomes. Moreover, rural residents have been shown to receive lower recommended care for AMI as compared to their urban counterparts. This dissertation advances prior research by examining the potential for HIT systems, namely CDSS, to reduce disparities in processes of care by supporting adherence to clinical guidelines. Previous research has been limited by small, single-institution studies and selection biases;therefore, this dissertation will use national datasets along with propensity scores and multilevel models to examine the true treatment effect on reducing health disparities by CDSS. PUBLIC HEALTH RELEVANCE: Integrating health information technology research with examinations of healthcare quality offers an innovative direction for addressing disparities in care based on race and residence. The work proposed here will focus on the associations between use of CDSS to support evidence-based medicine and (1) hospital adherence to clinical guidelines and health outcomes as measured by Hospital Compare from the Centers for Medicare and Medicaid (CMS) and (2) outcome quality disparities for vulnerable patients as measured by the Nationwide Inpatient Sample (NIS), Healthcare Cost and Utilization Project (HCUP), Agency for Healthcare Research and Quality. Policy makers will be able to use the results of this study to strengthen the case for fully functional electronic medical record (EMR) systems that include clinical decision support systems (CDSS).