Using Big Data to Optimize Treatment of Opioid Use Disorder in Pregnancy

Washington University, Saint Louis MO

Investigators

Linked publications & trials

Abstract

PROJECT SUMMARY I am an early career investigator in the fields of pharmacoepidemiology, population health, and addiction psychiatry. My overarching career goal is to become an independently funded researcher dedicated to investigating the real-world effectiveness of addiction medications so that we can address the gaps of the clinical trial literature with big data and reduce overdose. In this K08 award, I am interested in studying the comparative effectiveness and safety of FDA-approved pharmacotherapies (buprenorphine, methadone, naltrexone) to treat opioid use disorder during pregnancy, and assessing how the geographic landscape of treatment availability may be associated with their effectiveness against overdose across all American communities. The K08 award will support my early career training in the use of population health models, target trial emulation, and causal inference methods; address my mentorship and career development needs; and enable me to obtain the data required for my continued transition toward independence. In the proposed K08 research study, I will address the ongoing yet preventable epidemic of OUD-related overdose during pregnancy across states, geographies, and regions (urban vs rural). The specific aims of the study are (1) to evaluate access to opioid use disorder treatment for pregnant patients and identify communities, states, and regions with the highest rates of overdose and availability of FDA-approved pharmacotherapies; (2) to emulate a clinical trial using observational data to assess the comparative effectiveness of addiction treatments across communities in the U.S.; and (3) to examine population-level determinants of overdose as mechanisms underlying treatment outcomes during pregnancy. I will use a target trial emulation-based approach to achieve these aims, enriching existing Medicaid claims data with zip code-derived area-based characteristics to assess how population-based factors might influence treatment access and outcomes. The training and research experience I gain during the proposed K08 award period will be instrumental to my career trajectory, and the data generated in the proposed K08 study will be foundational to my planned applications for independent R01 funding, along with supporting NIDA's goal of developing new and improved strategies to prevent drug use and its consequences.