Predictors of antipsychotic medication change

Michael J. Sernyak, Douglas Leslie, Robert Rosenheck

Research output: Contribution to journalArticlepeer-review

6 Scopus citations

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 pro-cess, 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.

Original languageEnglish (US)
Pages (from-to)85-94
Number of pages10
JournalJournal of Behavioral Health Services and Research
Volume32
Issue number1
DOIs
StatePublished - Jan 2005

All Science Journal Classification (ASJC) codes

  • Health(social science)
  • Health Policy
  • Public Health, Environmental and Occupational Health

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