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PLoS One. 2018 Jul 19;13(7):e0198363. doi: 10.1371/journal.pone.0198363. eCollection 2018.

Patterns and predictors of off-label prescription of psychiatric drugs.

Author information

1
Yale University School of Medicine, New Haven, Connecticut, United States of America.
2
MGH/McLean Psychiatry Residency Program, Massachusetts General Hospital, Boston, MA, United States of America.
3
Harvard Medical School, Boston, MA, United States of America.
4
Section of General Internal Medicine and the National Clinician Scholars Program, Yale School of Medicine, New Haven, Connecticut, United States of America.
5
Department of Health Policy and Management, Yale School of Public Health, New Haven, Connecticut, United States of America.
6
The Center for Outcomes Research and Evaluation, Yale-New Haven Hospital, New Haven, Connecticut, United States of America.

Abstract

Off-label prescribing of psychiatric drugs is common, despite lacking strong scientific evidence of efficacy and potentially increasing risk for adverse events. The goal of this study was to characterize prevalence of off-label prescriptions of psychiatric drugs and examine patient and clinician predictors of off-label use. This manuscript presents a retrospective, cross-sectional study using data from the 2012 and 2013 National Ambulatory Medical Care Surveys (NAMCS). The study examined all adult outpatient visits to psychiatric practices for chronic care management with a single listed visit diagnosis in which at least one psychiatric drug was prescribed. The main outcome measure was off-label prescribing of at least one psychiatric drug, defined as prescription for a condition for which it has not been approved for use by the FDA. Among our sample representative of 1.85 billion outpatient visits, 18.5 million (1.3%) visits were to psychiatrists for chronic care management in which at least one psychiatric drug was prescribed. Overall, the rate of off-label use was 12.9% (95% CI: 12.2-15.7). The most common off-label uses were for manic-depressive psychosis treated with citalopram and primary insomnia treated with trazodone. Several patient and clinician characteristics were positively associated with off-label prescribing, including seeing a psychiatrist (OR: 1.06, 95% CI, 1.01-1.12; p = 0.03) instead of another type of clinician, the office visit taking place in the Western region of the country (OR: 1.09, 95% CI, 1.01-1.17; p = 0.02), and the patient having 3 or more chronic conditions (OR: 1.12, 95% CI, 1.02-1.14; p = 0.003). In contrast, having Medicare coverage (OR: 0.93, 95% CI, 0.84-0.97; p = 0.04) and receiving payment assistance from a medical charity (OR: 0.91, 95% CI, 0.88-0.96; p = 0.03) instead of private insurance were negatively associated with off-label prescribing. These results suggest that certain classes of psychiatric medications are being commonly prescribed to treat conditions for which they have not been determined by the FDA to be clinically efficacious and/or safe.

PMID:
30024873
PMCID:
PMC6053129
DOI:
10.1371/journal.pone.0198363
[Indexed for MEDLINE]
Free PMC Article

Conflict of interest statement

In the past 36 months, Dr. Ross has received research support through Yale University from Johnson and Johnson to develop methods of clinical trial data sharing, from Medtronic, Inc. and the Food and Drug Administration (FDA) to develop methods for postmarket surveillance of medical devices (U01FD004585), from the Food and Drug Administration to establish Yale-Mayo Clinic Center for Excellence in Regulatory Science and Innovation (CERSI) program (U01FD005938), from the Blue Cross Blue Shield Association to better understand medical technology evaluation, from the Centers of Medicare and Medicaid Services (CMS) to develop and maintain performance measures that are used for public reporting (HHSM 500-2013-13018I), from the Agency for Healthcare Research and Quality (R01HS022882), from the National Heart, Lung and Blood Institute of the National Institutes of Health (NIH) (R01HS025164), and from the Laura and John Arnold Foundation to establish the Good Pharma Scorecard at Bioethics International and the Collaboration for Research Integrity and Transparency (CRIT) at Yale University. This does not alter our adherence to PLOS ONE policies on sharing data and materials.

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