PROJECT SUMMARY/ABSTRACT
Opioid overdoses continue to increase and disproportionately influence people experiencing
greater social risk factors. Buprenorphine is a first-line treatment for opioid use disorder (OUD)
that decreases opioid overdoses, especially when initiated in the emergency department (ED)—
a high volume point-of-care. However, buprenorphine treatment inequities exist in and outside
of the ED, and methodological challenges make it difficult to identify vulnerable populations with
OUD who may benefit from improved access to, and quality of, buprenorphine treatment.
The social vulnerability index (SVI), developed by the Centers for Disease Control and
Prevention (CDC), is a measure that identifies vulnerable populations by capturing social risk
factors in a region that influence health. A composite score is derived based on an area’s: 1)
socioeconomic status; 2) household composition and disability; 3) minority status and language;
4) housing and transportation. Studies that examined the influence of area-level social risk
factors on buprenorphine treatment and opioid overdoses were state specific or limited to
county-level measures. No studies have examined the influence of social vulnerability on
buprenorphine treatment and opioid overdoses following an opioid-related ED visit in people
with OUD who have commercial or Medicare Advantage (aged and disabled) health insurance.
This study will deploy the SVI at the residential zip-code level to investigate the influence of
social vulnerability on buprenorphine treatment and opioid overdoses following an opioid-related
ED visit using claims data (OptumLabs® Data Warehouse) from people with commercial or
Medicare Advantage health insurance. Aim 1 will employ Cox hazard regression analysis to
assess whether social vulnerability is associated with time to initiating buprenorphine treatment.
Aim 2 will estimate the effect of social vulnerability on buprenorphine treatment retention for at
least 180 days, as well as eight other buprenorphine treatment quality measures from the
American Society of Addiction Medicine (ASAM), using generalized estimating equations (GEE).
Aim 3 will estimate the effect of prescribing practices on opioid overdoses using GEE. The
results from this study will serve as a model for future research and inform targeted policy and
clinical levers that improve access to, and quality of, buprenorphine treatment, as well as opioid-
related outcomes, among people with OUD experiencing greater social risk factors.
