Application of a diazepam milligram equivalency algorithm to assess benzodiazepine dose intensity in Rhode Island in 2018

Abstract

BACKGROUND: Benzodiazepines are indicated for the treatment of many conditions, such as anxiety disorders, muscle spasms, alcohol withdrawal, agitation, movement disorders, and epilepsy, and are one of the most frequently prescribed medication classes. This class of medication has important safety considerations, including an increased risk of dependence and addiction, falls, and death from opioid overdose. Although benzodiazepine safety and prescribing encompasses a rich and important research area, there is a lack of pharmacoepidemiologic literature addressing benzodiazepine dosing intensity in real-world settings. OBJECTIVE: To develop and apply a standardized benzodiazepine milligram equivalency conversion algorithm and assess the dose intensity of benzodiazepine use in Rhode Island (RI) in 2018. METHODS: A systematic literature review was conducted to identify the most commonly used benzodiazepine equivalency values. We then conducted a cross-sectional analysis of 2018 data from the RI Prescription Drug Monitoring Program (PDMP) to calculate the mean daily diazepam milligram equivalency (DME) based on a patient's most recent dispensing. A multivariable logistic regression analysis was conducted to determine the association between higher benzodiazepine doses (≥ 15 DME/day) and recipient characteristics, including concurrent use of opioids or stimulants. RESULTS: We identified 143,026 patients who received at least 1 prescription for a benzodiazepine in RI in 2018. The mean (SD) daily DME was 10.60 (9.05), and 26.2% of individuals had a mean DME per day of at least 15. Approximately 14% (n = 20,168) of patients prescribed a benzodiazepine had concurrent use with a prescription opioid, and 6.7% (n = 9,547) had concurrent use with a prescription stimulant. Females had a 28% lower adjusted odds of receiving a benzodiazepine dose of at least 15 DME per day compared with males (adjusted odds ratio [aOR] = 0.72, 95% CI = 0.70-0.73). The adjusted odds of receiving a benzodiazepine prescription of at least 15 DME per day was lower among the younger (aged 18-34 years) and older age groups (aged 65 years and older) compared with patients aged 35-64 years. Compared with commercial insurance, all other forms of payment had significantly higher adjusted odds of a daily benzodiazepine dose of at least 15 DME per day. The adjusted odds receiving a daily DME of at least 15 was 67% higher among those who also received a concurrent pharmacy dispensing for an opioid and 84% higher among those who also received a concurrent dispensing for a stimulant drug (aOR = 1.67, 95% CI = 1.61-1.72; aOR = 1.84, 95% CI = 1.76-1.93, respectively). CONCLUSIONS: Individuals aged 35-64 years with Medicaid insurance and those aged under 65 years with Medicare were more likely to be prescribed a benzodiazepine of at least 15 DME per day. Higher benzodiazepine DMEs were also dispensed to patients who concurrently used prescription opioids or stimulants who may be at increased risk of medication-related harm. We advocate for routine measurement of benzodiazepine dose intensity as a risk reduction strategy. DISCLOSURES: No funding supported this study. The authors have no conflicts of interest to disclose. The content and results of this study are solely the responsibility of the authors and do not necessarily represent the official views of the Rhode Island Department of Health. Kogut is partially supported by Institutional Development Award Numbers U54GM115677 and P20GM125507 from the National Institute of General Medical Sciences of the National Institutes of Health, which funds Advance Clinical and Translational Research (Advance-CTR) and the RI Lifespan Center of Biomedical Research Excellence (COBRE) on Opioids and Overdose, respectively. The content of this study is solely the responsibility of the authors and does not necessarily represent the official views of the National Institutes of Health. Contents of this study were presented as a poster presentation at AMCP 2019 Nexus; October 29-November 1, 2019; National Harbor, MD.

FIGURE 1

Sample Identification Flowchart