Panel Paper: Out-of-Pocket Payments and Naloxone Utilization, 2015-2018

Saturday, November 9, 2019
I.M Pei Tower: Majestic Level, Vail (Sheraton Denver Downtown)

*Names in bold indicate Presenter

Zeid S. El-Kilani, Jessica White, Meena Vythilingam and Brett Giroir, U.S. Department of Health and Human Services

Naloxone is a life-saving treatment for individuals experiencing an opioid-related overdose. As a result, the US government has made access to naloxone a key component in combating the opioid epidemic. Despite the important role naloxone can play in saying lives, little is known about how insurance coverage impacts patient access to naloxone. This research helps the field understand how out-of-pocket payments and insurance benefit design influence naloxone utilization as well as the opportunities that may exist for promoting greater access to naloxone products. This study examines out-of-pocket payments for naloxone products to understand how payers structure their benefit designs for naloxone products and the potential impacts of out-of-pocket payments on prescription abandonment. This study primarily analyzes data from IQVIA’s Formulary Impact Analyzer (FIA). FIA is a pharmaceutical claims database that provides information on paid, substituted, rejected, and abandoned pharmaceutical claims for all types of payers. The database includes information related to the primary payer, potential additional payers, and the out-of-pocket payments of the patient. The main purpose of this dataset is to evaluate the impact of formulary management techniques and out-of-pocket payments on access. In particular, the study examines the impacts of out-pocket-payments on utilization. The main dependent variable is a categorical variable indicating if the naloxone prescription was abandoned. The main independent variable is the out-pocket payment for the prescription. Using logistic regressions, we examine how out-of-pocket payments influence the likelihood of naloxone prescription abandonment. Covariates in the model include strength of most recent opioid prescription in the last two months, if the naloxone prescription was co-prescribed with the opioid prescription, the state in which the prescription was filled, median income in the patient’s county, if the prescription was filled after statewide implementation of a naloxone standing order, and other variables that may influence the demand for naloxone.