GEOGRAPHIC ACCESS AND SERVICE USE IN RURAL DEPRESSION

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We propose to 1) examine the effects of geographical accessibility on the utilization of mental health services in rural areas and 2) to develop and test predictive spatial models of treatment seeking behavior. Analyses will be conducted using a previously compiled population-based longitudinal dataset of 470 subjects with current substantial symptoms of depression. Geographical accessibility is defined as the road travel distance from each patient to primary care and specialty mental health care providers. To operationalize this construct we will collect locational information for every health care provider in the study area. We hypothesize that individuals living further away from providers will be less likely to seek care for their symptoms of depression. For individuals unsuccessfully treated in the primary care setting, we hypothesize that those with poor geographical accessibility to specialty mental health providers will be less likely to be referred by their primary care physician to the specialty mental health sector. These hypotheses will be tested using models of treatment seeking behavior that are a function of patient predisposing, enabling and need characteristics, and provider practice attributes especially location. This proposed research design constitutes a major improvement over prior studies which have approximated geographical accessibility with a simple rural/urban dichotomous explanatory variable. The statistical models created to test these hypotheses will be used to develop a system of integrated models able to predict aggregate utilization patterns from census data. These predictive models will be externally validated by comparing predicted and actual utilization in a different treatment-based sample of patients seen by ten primary care physicians practicing in rural areas throughout Arkansas. The proposed study is a policy relevant research topic for health care reform because the geographic distribution of mental health care services can be modified by public policy. The predictive models developed here could theoretically be used to forecast changes in aggregate utilization following a spatial redistribution of mental health care providers and facilities. The relative importance of geographical accessibility as a treatment barrier is likely to increase if other aspects of access, such as lack of insurance coverage, are reduced under the auspices of health care reform.