# Variation in the Use of Opioid Agonist Treatment in Hospitals

> **NIH NIH F30** · OREGON HEALTH & SCIENCE UNIVERSITY · 2020 · $50,520

## Abstract

PROJECT SUMMARY/ABSTRACT
Persons with opioid use disorder (OUD) have longer and more expensive hospitalizations (over $15 billion
annually) than general hospital admissions. Despite the magnitude of this issue, little research describes
hospital use of evidence-based opioid agonist treatments (OATs). I propose to assess hospital variation, model
associations with patient and hospital attributes, and explore hospital structures influencing OAT delivery in the
context of local and broader environments. There are three OAT (continuation of pre-hospital OAT, OAT for
withdrawal management, and OAT initiation for long-term care) and three non-OAT (short-acting opioids,
symptom management medications, and other care) OUD care scenarios. I will measure patient disposition
and 30-day readmissions for each care scenario. This study leverages health service delivery conceptual
frameworks and a multilevel change model using a mixed methods approach. The study addresses two
quantitative aims (analysis of OUD hospital admissions in the Premier Healthcare Database) and one
qualitative aim (interviews with 20 hospital key informants from a purposive sample of 10 to 12 hospitals).
Specific Aim 1. Assess variation in hospital OAT delivery and test the associations of OAT and non-
OAT care scenarios with attributes and outcomes. I will evaluate whether meaningful variation exists in
hospital OAT delivery and whether patient attributes (e.g., gender), hospital attributes (e.g., size) and patient
outcomes (e.g., disposition) are associated with the provision of OAT in the hospital.
H1a: Measurable differences exist among hospital OAT quartiles and between top and bottom OAT quartiles.
H1b: Hospital OAT quartiles will be associated with at least one patient attribute, one hospital attribute, and
one patient outcome domain.
Specific Aim 2. Model and test the proposed relationships of patient and hospital attributes on
hospital OAT delivery and patient outcomes. I will use multilevel modeling to identify specific associations
of patient (e.g., race) and hospital (e.g., teaching status) attributes with hospital OAT variation, patient
outcomes, and between-hospital variation.
H2a: OAT delivery will be negatively associated with patient race (non-white), insurance status (uninsured),
and hospital teaching status (non-teaching).
H2b: In-hospital mortality and 30-day readmissions will be negatively associated with hospital OAT delivery.
Specific Aim 3. Use qualitative interviews with key hospital informants to explore the environmental
context and hospital structures that may mediate hospital OAT delivery. Findings from Aims 1 and 2
guide the purposive sampling and interview protocol for the key informant interviews. I will probe for local
hospital (e.g., addiction medicine fellowship) and broader environmental contextual factors (e.g., federal policy)
that may influence hospital structures (e.g., formulary) impeding or facilitating hospital OAT delivery.

## Key facts

- **NIH application ID:** 9954042
- **Project number:** 5F30DA044700-04
- **Recipient organization:** OREGON HEALTH & SCIENCE UNIVERSITY
- **Principal Investigator:** Kelsey Caroline Priest
- **Activity code:** F30 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2020
- **Award amount:** $50,520
- **Award type:** 5
- **Project period:** 2017-07-01 → 2021-06-30

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/9954042

## Citation

> US National Institutes of Health, RePORTER application 9954042, Variation in the Use of Opioid Agonist Treatment in Hospitals (5F30DA044700-04). Retrieved via AI Analytics 2026-05-24 from https://api.ai-analytics.org/grant/nih/9954042. Licensed CC0.

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