# Real-world complexities in opioid use disorder treatment: understanding family comorbidity, high-risk medication use, and costs related to treatment adherence and health outcomes

> **NIH NIH K01** · UNIVERSITY OF CALIFORNIA LOS ANGELES · 2022 · $182,939

## Abstract

PROJECT SUMMARY
Medications for opioid use disorder (MOUD) have the potential to improve the health and well-being of more
than 2.1 million Americans with OUD, however, long-term adherence particularly to buprenorphine is alarmingly
poor. Pain, mental health, and substance use disorders are increasingly recognized as risk factors for inadequate
treatment adherence and often co-occur in families due to shared genetic and environmental factors.
Understanding comorbidities in patients with OUD and their family members, and the impact of these
comorbidities on poor opioid use outcomes, can help identify patients at risk for inadequate treatment adherence
and serious adverse events. Further, information on the costs associated with buprenorphine non-adherence
and family comorbidities can inform health insurance reimbursement policies. The overall career goal of the
recipient is to become a leading pharmacoepidemiologist focused on improving treatment for substance use
disorders, particularly opioid use disorders. The goal of this K01 is to train the recipient to investigate associations
between family comorbidities and/or prescription medications with a high risk of misuse and buprenorphine
treatment adherence, opioid use outcomes, and costs to the family unit and health insurer. Research aims of
this project are to: (1) develop a clinically relevant prediction model to identify patients prescribed buprenorphine
at risk of inadequate adherence; (2) determine whether other prescriptions in the family are associated with poor
buprenorphine adherence and opioid-related adverse events; and (3) compare overall healthcare costs to the
family and health insurer across varying levels of buprenorphine adherence. The training aims of this project are
to: (1) gain understanding of the clinical assessment and diagnosis of opioid use disorders and comorbid mental
health conditions; (2) learn and apply innovative methods for dyadic data analyses; (3) learn and apply methods
for conducting economic evaluations of substance use treatment; (4) hone professional skills in research,
publishing, and project administration; and (5) responsible conduct of research. Training aims will be pursued
through tutorials with world-renowned experts forming the recipient's mentorship team, graduate-level
coursework, workshops and seminars, participation in scientific meetings, and mentored research. Research
aims will be accomplished using the OptumLabs Data Warehouse, a large integrated commercial healthcare
insurance claims database that tracks beneficiaries, spouses, and dependents across health plans and over
time. This project will fill an important gap in our understanding of how family comorbidities and medication use
by family members influence MOUD treatment adherence, outcomes, and costs, and will provide evidence to
support interventions by clinicians and health insurers to improve MOUD adherence outcomes.

## Key facts

- **NIH application ID:** 10449784
- **Project number:** 1K01DA054359-01A1
- **Recipient organization:** UNIVERSITY OF CALIFORNIA LOS ANGELES
- **Principal Investigator:** Marissa J Seamans
- **Activity code:** K01 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2022
- **Award amount:** $182,939
- **Award type:** 1
- **Project period:** 2022-04-01 → 2027-03-31

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10449784

## Citation

> US National Institutes of Health, RePORTER application 10449784, Real-world complexities in opioid use disorder treatment: understanding family comorbidity, high-risk medication use, and costs related to treatment adherence and health outcomes (1K01DA054359-01A1). Retrieved via AI Analytics 2026-05-23 from https://api.ai-analytics.org/grant/nih/10449784. Licensed CC0.

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