Abstract
Atypical antipsychotics account for more than 60% of antipsychotic prescriptions written for the treatment of schizophrenia. While switching from one antipsychotic to another is a dynamic process, there has been no research on individual patient and institutional characteristics that predict antipsychotic switching. VA national administrative data were used to identify patients (n=9660) with schizophrenia maintained on antipsychotic medication. Logistic regression was used to identify predictors of medication switching. Independent variables included information about service utilization, sociodemographic and clinical variables as well as institutional characteristics. This model was repeated for more specific switches between classes of medications and between specific medications. High levels of outpatient and inpatient service use were the most powerful predictors of switching. Sociodemographic, institutional, diagnostic, and functional measures were also predictive in some cases. Controlling for independent sociodemographic, diagnostic, and functional measures, frequency of clinical contact was the most robust predictor of switching antipsychotics.
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Dr Sernyak has served on an advisory board for Janssen and Lilly. He is on the speakers' bureau of Pfizer. He has received financial support for the work described in this article from AstraZeneca.
Dr Rosenheck is a consultant to Bristol Meyers Squibb and receives grant support from Janssen, Lilly, and AstraZeneca.
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Sernyak, M.J., Leslie, D. & Rosenheck, R. Predictors of antipsychotic medication change. The Journal of Behavioral Health Services & Research 32, 85–94 (2005). https://doi.org/10.1007/BF02287330
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DOI: https://doi.org/10.1007/BF02287330