The Ability of Aggregate Data to Predict Self‐Sufficiency Levels in Subsidized Rural Primary Care Practices

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Abstract
American rural health policy has as its long-term goal the reallocation of health facilities and manpower to permit equitable access to primary care for all citizens. Rural health centers subsidized by governmental and philanthropic programs frequently have been placed in places of high need for their services. Yet both government and philanthropic policymakers expect these primary care practices to become economically self-sufficient within a few years of practice. The problem is how to assign rural practices to communities with a planning process that will enhance the likelihood that these conflicting goals of serving need and financial self-sufficiency will be achieved. This study uses actual 1980 self-sufficiency data from 167 randomly selected rural primary care clinics as the dependent variable. Independent variables for the corresponding communities five or more years earlier were taken from a database often used by policymakers to make site evaluations. These data tend to be selected from aggregate county level measures. Regression analysis were used to determine how well these data could predict actual self-sufficiency in later years. The result of the analysis is that these aggregate level data have little capacity to predict the ability of rural primary care practices to achieve self-sufficiency. Much better predictions can be made on the basis of local, practice-specific variables. Therefore, planning for economically viable rural practices calls for a much different forecasting approach.