Healthy Skepticism Library item: 4925

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Publication type: Journal Article

Lasser KE, Seger DL, Yu DT, Karson AS, Fiskio JM, Seger AC, Shah NR, Gandhi TK, Rothschild JM, Bates DW.
Adherence to black box warnings for prescription medications in outpatients.
Arch Intern Med 2006 Feb 13; 166:(3):338-44
http://archinte.ama-assn.org/cgi/content/full/166/3/338

Abstract:

BACKGROUND: Few data are available regarding the prevalence of potentially dangerous drug-drug, drug-laboratory, and drug-disease interactions among outpatients. Our objectives were to determine how frequently clinicians prescribe drugs in violation of black box warnings for these issues and to determine how frequently such prescribing results in harm. METHODS: In an observational study of 51 outpatient practices using an electronic health record, we measured the frequency with which patients received prescriptions in violation of black box warnings for drug-drug, drug-laboratory, and/or drug-disease interactions. We performed medical record reviews in a sample of patients to detect adverse drug events. Multivariate analysis was conducted to assess the relationship of prescribing in violation of black box warnings to patient and clinician characteristics, adjusting for potential confounders and clustering. RESULTS: Of 324 548 outpatients who received a medication in 2002, 2354 (0.7%) received a prescription in violation of a black box warning. After adjustment, receipt of medication in violation of a black box warning was more likely when patients were 75 years or older or female. The number of medications taken, the number of medical problems, and the site of care were also associated with violations. Less than 1% of patients who received a drug in violation of a black box warning had an adverse drug event as a result. CONCLUSIONS: About 7 in 1000 outpatients received a prescription violating a black box warning. Few incidents resulted in detectable harm.

Keywords:
Adolescent Adult Adverse Drug Reaction Reporting Systems Age Factors Aged Ambulatory Care* Boston Drug Labeling* Female Humans Male Medical Records Systems, Computerized Middle Aged Multivariate Analysis Pharmaceutical Preparations/adverse effects* Physician's Practice Patterns/statistics & numerical data* Prescriptions, Drug/statistics & numerical data* Research Support, Non-U.S. Gov't Sex Factors