ABSTRACT
Spatial data analysis is playing an increasingly important role in health services research, enabling policy makers to better understand the health needs of communities, to identify barriers to health care, and to allocate health resources in a cost-effective manner. To date, spatial models have been used to explore geographic variation in hospital referral rates (Congdon, 2006; Congdon and Best, 2000), emergency department visits (Congdon, 2006; Neelon et al., 2014, 2013), and access to primary care services (Mobley et al., 2006). Spatial methods have also been developed to examine geographic and temporal trends in health services costs and patient medical expenditures (Moscone et al., 2007; Moscone and Knapp, 2005; Neelon et al., 2015a, 2015b). These efforts continue to inform policy decisions and guide community-based efforts to improve access to health care.
