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Diagnoses associated with use of atypical antipsychotics in a commercial health plan: a claims database analysis.

Content Provider	World Health Organization (WHO)-Global Index Medicus
Author	Citrome, Leslie Kalsekar, Iftekhar Guo, Zhenchao Laubmeier, Kimberly Hebden, Tony
Spatial Coverage	United States
Description	Author Affiliation: Citrome L ( Department of Psychiatry and Behavioral Sciences, New York Medical College, Valhalla, New York. Electronic address: citrome@cnsconsultant.com.); Kalsekar I ( Bristol-Myers Squibb, Plainsboro, New Jersey.); Guo Z ( Bristol-Myers Squibb, Plainsboro, New Jersey.); Laubmeier K ( Otsuka America Pharmaceutical, Inc., Princeton, New Jersey.); Hebden T ( Bristol-Myers Squibb, Plainsboro, New Jersey.)
Abstract	BACKGROUND: Atypical antipsychotics are indicated for specific psychiatric conditions; however, they are frequently used for US Food and Drug Administration-nonapproved indications. OBJECTIVE: This study assessed the types of medical diagnoses associated with atypical antipsychotic prescriptions in commercial health care plans. METHODS: This retrospective cohort study used the OptumInsight commercial data set from January 2008 to June 2011. The index date was defined as the earliest date of prescription for the atypical antipsychotics aripiprazole, olanzapine, quetiapine, risperidone, and ziprasidone, from January 1, 2009, through June 30, 2010. Medical claims during a 2-year period (12 months before and 12 months after the index date) were used to identify relevant diagnostic codes from the International Classification of Diseases, Ninth Edition, Clinical Modification associated with the antipsychotic prescription. A logistic regression analysis was conducted to examine the predictors of use of atypical antipsychotics without a relevant diagnosis, that is, schizophrenia, bipolar, or major depressive disorder (MDD). RESULTS: Of 18,352 patients included in the analysis, 3593 (19.5%) who filled a prescription for atypical antipsychotics did not have an approved diagnosis. Off-label utilization varied, with approximately a quarter of patients with prescriptions for quetiapine (24.1%), risperidone (23.1%), or olanzapine (21.8%) being without a relevant diagnostic code, whereas proportions were lower for patients prescribed aripiprazole (14.0%) or ziprasidone (13.1%). Of those with a psychiatric disorder other than schizophrenia, bipolar disorder, or MDD, approximately a third of prescriptions were for anxiety disorders, with similar proportions across all atypical antipsychotics. Patients were often prescribed quetiapine for substance abuse (22.7%), whereas patients with 'other psychiatric conditions' were prescribed risperidone (26.3%) or ziprasidone (25.0%). The logistic regression analysis indicated that patients prescribed olanzapine, quetiapine, or risperidone were significantly more likely to have no diagnostic code for schizophrenia, bipolar disorder, or MDD compared with patients prescribed aripiprazole. CONCLUSION: Nearly a fifth of commercially insured patients were prescribed atypical antipsychotics, in particular, olanzapine, quetiapine, or risperidone, for diagnoses that were not aligned with US Food and Drug Administration-approved indications.
File Format	HTM / HTML
ISSN	01492918
Issue Number	12
Volume Number	35
e-ISSN	1879114X
Journal	Clinical Therapeutics
Language	English
Publisher	Elsevier
Publisher Date	2013-12-01
Publisher Place	United States
Access Restriction	One Nation One Subscription (ONOS)
Subject Keyword	Discipline Pharmacology Antipsychotic Agents Therapeutic Use Drug Prescriptions Insurance Claim Review Mental Disorders Drug Therapy Adolescent Adult Economics Bipolar Disorder Databases, Factual Depressive Disorder, Major Female Health Care Costs Humans Logistic Models Male Middle Aged Off-label Use Retrospective Studies Schizophrenia United States Young Adult Journal Article Research Support, Non-u.s. Gov't
Content Type	Text
Resource Type	Article
Subject	Pharmacology Pharmacology (medical)

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Diagnoses associated with use of atypical antipsychotics in a commercial health plan: a claims database analysis.