# Project INSPIRE – (Interprofessional Simulation Program for Clinical Resilience and Empathy) for healthcare teams caring for birthing individuals with substance use disorder in Utah

> **NIH NIH U54** · UTAH STATE HIGHER EDUCATION SYSTEM--UNIVERSITY OF UTAH · 2024 · $977,951

## Abstract

PROJECT SUMMARY / ABSTRACT: PROJECT 2 INSPIRE
Individuals with substance use disorder (SUD) face a higher risk of severe maternal morbidity and mortality.
Provider bias and stigma contribute to these outcomes by attenuating the provision of evidence-based, person-
centered care. The goal of this study is to develop and evaluate INSPIRE, an intervention for interprofessional
healthcare teams to improve care for individuals with substance use disorder (SUD) during their peri-delivery
care. INSPIRE is envisioned as a modular intervention, adaptive to the needs of individual providers. It will
include three core modules (a webinar on SUD in birth, an in-person simulation training, and patient vignettes
with real-time feedback on clinical empathy skills using artificial intelligence technology). Booster modules will
be delivered based on provider response across core constructs (bias, burnout, clinical empathy). In AIM 1, we
will use rigorous qualitative methods to examine bias and stigma in obstetric care for pregnant and birthing
individuals with SUD from provider and patient perspectives. In AIM 2, we will apply these data to develop the
INSPIRE intervention. Working with a stakeholder advisory board, we will adapt simulation training curricula for
the SUD context, and develop additional modules focused on clinical empathy, bias and stigma, and burnout.
Using human centered design principles, we will prototype modules with facilities around the state of Utah. In
AIM 3, we will evaluate INSPIRE at the University of Utah hospital using a quasi-experimental design to
determine: a) impact on healthcare team outcomes, b) impact on patient outcomes, and c) potential for
scalability. We will enroll 400 healthcare team members across clinical specialties that support birthing
individuals. All enrolled providers will receive INSPIRE, and assessments will be conducted at baseline, 2
months, and 6 months. The primary outcome for providers is bias, using the Medical Conditions Regard Scale
(MCRS). We will assess change in MCRS scores from baseline to 6 months using a mixed effects linear
regression model, specified to provide a paired-sample comparison between pre- and post-intervention scores.
To assess patient level outcomes, we will enroll patients with SUD giving birth in two time periods: pre-
intervention (n=100) and post-intervention (n=100). Patient surveys will be conducted in person, prior to
discharge from labor and delivery, and medical record data will be abstracted up to 6 months postpartum. The
primary outcome for patients will be self-reported Person-Centered Maternity Care (PCMC). We will use linear
regression to examine differences in PCMC scores between baseline and endline, controlling for potential
confounders. We will apply the RE-AIM implementation science framework to assess potential for program
scale-up. In Years 6-7, we will support the ELEVATE Center in statewide dissemination and implementation of
INSPIRE. We will train facility-le...

## Key facts

- **NIH application ID:** 10908718
- **Project number:** 5U54HD113169-02
- **Recipient organization:** UTAH STATE HIGHER EDUCATION SYSTEM--UNIVERSITY OF UTAH
- **Principal Investigator:** Susanna Rose Cohen
- **Activity code:** U54 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2024
- **Award amount:** $977,951
- **Award type:** 5
- **Project period:** 2023-08-17 → 2030-07-31

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10908718

## Citation

> US National Institutes of Health, RePORTER application 10908718, Project INSPIRE – (Interprofessional Simulation Program for Clinical Resilience and Empathy) for healthcare teams caring for birthing individuals with substance use disorder in Utah (5U54HD113169-02). Retrieved via AI Analytics 2026-05-23 from https://api.ai-analytics.org/grant/nih/10908718. Licensed CC0.

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