Duke 2008 | ASHE | Equity and Efficiency in Health and Healthcare

The last decade has witnessed unprecedented growth in new technologies for mental health treatment, but the rate at which these products have spread through the market has been uneven. Providers may learn about new treatments or gain information on existing treatments from other providers within networks, which vary by specialty. In order to advance models of best practice, it is important to understand the factors that underlie these varying rates of diffusion. The purpose of this paper is to examine the diffusion of antipsychotic medication in subpopulations defined by provider-level characteristics such as specialty and region and a measure of the close-knittedness of physician networks. Data are drawn from the Florida Medicaid program for 1994-2005. We convert medication use into Defined Daily Dose units. The close-knittedness of physician networks is determined using the degree of association in antidepressant use by other members of the network. We use a fourth-order polynomial approach to model the diffusion curve with a fixed start date and to allow for the variety of shapes, including sigmoid as well as concave, that diffusion curves may actually take on, using the degree of close-knittedness of social networks as a key explanatory variable. We use several different measures of antipsychotic diffusion, including the percent of all antipsychotic medications accounted for by the newer atypical class and the percent of antipsychotic medications prescribed based on market age (< 2 years, 2-5 years, and >5 years). We find that providers differ in their involvement in social networks and diffusion curves differ substantially across provider types, but almost all models show that antipsychotic medications have faster rates, but not necessarily levels, of diffusion in close-knit physician networks.