# Data Science to Inform Coordinated Behavioral Health and HIV Care Re-Engagement

> **NIH NIH P30** · UNIVERSITY OF WASHINGTON · 2022 · $286,168

## Abstract

PROJECT SUMMARY / ABSTRACT
Engaging the most marginalized people with HIV (PWH) in treatment is crucial to end the HIV epidemic in the
U.S. The Ending the HIV Epidemic (EHE) strategy in King County, Washington is designed to improve HIV
services for people with complex barriers to care, including homelessness or unstable housing, severe mental
illness, and substance use disorders. The health department in King County has developed a robust information
exchange system with data from HIV surveillance, jail booking, and emergency room visits to guide public health
interventions to re-engage PWH in care (“Data to Care”). The overall goals of the proposed project are to use
data science to improve public health Data to Care activities and to establish a community-engaged partnership
team that will collaboratively develop a future data-guided mobile outreach & treatment team for high-need PWH.
For Aim 1, we will develop and validate an algorithm to prioritize individual PWH for interventions to improve
engagement in HIV care and behavioral health services. Using a machine learning method (classification and
regression tree models), we will analyze data from >14 years of case investigations and the current health
department information exchange system. During the project year, we will newly integrate behavioral health and
housing data into the information exchange. Throughout this work, we will incorporate input from our community
partners on our use of data for care re-engagement. For Aim 2, we will establish a community-engaged
partnership team to develop a mobile outreach & treatment intervention for high-need PWH in King County. This
team will include representatives of key service agencies and the health department, people with lived
experience, and university researchers. We will use the Transcreation Framework for community-engaged
implementation science research to develop a mobile outreach and engagement team based on the Assertive
Community Treatment approach, an evidence-based service delivery model that uses a multidisciplinary team
to deliver community-based mental health treatment to individuals with severe mental illness. The expected
outcomes of this project include: 1) a validated case prioritization algorithm for HIV care re-engagement
interventions that will immediately inform health department Data to Care efforts and guide a future mobile
outreach & treatment team; 2) a solidified partnership of community agencies, community members with lived
experience, the health department, and researchers, which will collaboratively implement and evaluate the future
mobile outreach & treatment team; and 3) a refined intervention, implementation strategy, and implementation
research logic model to be used in a grant proposal to study the data-guided mobile outreach & treatment team.

## Key facts

- **NIH application ID:** 10599453
- **Project number:** 3P30MH123248-02S3
- **Recipient organization:** UNIVERSITY OF WASHINGTON
- **Principal Investigator:** Jane M. Simoni
- **Activity code:** P30 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2022
- **Award amount:** $286,168
- **Award type:** 3
- **Project period:** 2021-04-01 → 2025-02-28

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10599453

## Citation

> US National Institutes of Health, RePORTER application 10599453, Data Science to Inform Coordinated Behavioral Health and HIV Care Re-Engagement (3P30MH123248-02S3). Retrieved via AI Analytics 2026-05-26 from https://api.ai-analytics.org/grant/nih/10599453. Licensed CC0.

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