Understanding the Economic Losses Resulting From Opioid Overdose Deaths in the USA Between 2018-2020

Shalinie Mahadeo, BA1, Briana Lui, BS1 , Elizabeth Khusid, BA1, Marisa Weber, MD2, Rohan Jotwani, MD2, Marguerite Hoyler, MD2, and Robert White, MD2

1MD Program, Weill Cornell Medicine, New York, NY USA, 2Department of Anesthesiology, Weill Cornell Medicine, New York, NY USA

 

Background

Opioids—mainly synthetic opioids (other than methadone)—are currently the main driver of drug overdose deaths, with fentanyl taking over as the nexus of this epidemic. Our knowledge of the pharmacodynamics of these drugs that make them highly addictive continues to grow, as does our understanding of the psychosocial implications of this crisis. Although prior studies have assessed the economic impacts of total overdose deaths at a regional level, there remains a paucity of information regarding the financial burdens due to specific types of opioids at a national level.

The aim of the paper is to examine the economic burdens of the opioid overdose crisis by quantifying years of potential lives lost (YPLL) due to premature mortality and the value of those statistical lives (VSL) to estimate monetary losses to the economy. We hypothesize that fentanyl will contribute a significant portion of financial burdens from overdose deaths.

 

Methods

The total number of deaths from drug overdoses from fentanyl, hydrocodone, hydromorphone, oxycodone, and oxymorphone was extracted from the National Vital Statistics System (NVSS) for 2018-2020 (1). The data were stratified by age range and gender. Period life expectancy was extracted from the 2019 actuarial life tables from the Social Security Administration website. Period life expectancy is defined as the average number of years of life remaining if a group of persons at that age were to experience the mortality rates for 2017 over the course of their remaining life.

The baseline age of death was calculated by taking the upper value of the midpoint for each age range. Annual YPLL for each age range was calculated by multiplying the number of deaths by the 2019 period life expectancy for males and females at the midpoint of each respective age range. The population average value of statistical life year (VSLY), which is used by policymakers to calculate the economic value of reducing mortality risks, was determined to be US$240,676 based on previously published literature. The VSL for each age range was then calculated by multiplying the YPLL by the VSLY to quantify the economic burden of these premature deaths.