Abstract

Limited evidence exists regarding the risks and benefits of antipsychotic (AP) polypharmacy, however, antipsychotic polypharmacy is not uncommon and is compounded by widespread off-label prescribing. This study uses repeatable methods and real world data to profile AP users and track AP treatment patterns, polypharmacy and hospitalization and side effect risks. Five years of integrated pharmacy and medical claims from a large U.S pharmacy benefits manager from 2008-2012 provide real world treatment patterns among atypical, second generation and conventional APs. Medication utilization schizophrenia diagnosis (ICD9 295.*) compared to patients with depressive disorder NOS (ICD9 311). Switching and augmentation assignment are compared by various ‘allowable gaps’ used to define periods ‘on therapy’ and by requiring at least 1, 2 or 4 prescriptions of second-line treatment. Duration of therapy, risk of hospitalization, extrapyramidal disorder, dyslipidaemia, somnolence, anticholinergic syndrome, and seizures are compared between monotherapy and polytherapy patients. Anti-psychotic treatment patterns, demographics and top comorbidities are explored for treated schizophrenics and treated patients with NOS diagnoses. Only 20% of atypical antipsychotic users continue therapy for more than a year, with more than half discontinuing therapy within three months of initiation. Polypharmacy rates varied between 1% and 4% of the population depending allowable gap and the number of prescriptions required for a switch. All cause hospitalizations and anti-psychotic-specific side effect rates for monotherapy (6,063 risperidone and 14,930 quetiapine) users are compared to polypharmacy (2,180 risperidone and 3,798 quetiapine) users reveal that monotherapy populations were less likely to be hospitalized and have side effects. Higher hospitalization and side effect rates were found among polypharmacy users, but could be related to unsafe polypharmacy or disease severity and varied by polypharmacy definition. More evidence using well documented methods and metrics implemented on worldwide real world datasets could help monitor treatment patterns and gather evidence toward optimizing psychiatric care.

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