# Designing Differentiated PrEP Service Delivery Models for Implementation in New York City Emergency Departments through a Community Collaborative

> **NIH NIH P30** · NEW YORK STATE PSYCHIATRIC INSTITUTE DBA RESEARCH FOUNDATION FOR MENTAL HYGIENE, INC · 2021 · $354,248

## Abstract

PROJECT SUMMARY. HIV pre-exposure prophylaxis (PrEP) is a highly effective method to decrease HIV
transmission that remains underutilized. This submission is a planning project to engage a Community
Collaborative of providers and users of ED services, community-based organization (CBO) staff, and
policymakers to develop a set of strategies to incorporate PrEP services in Emergency Departments (EDs) in
the four most highly burdened counties in New York State. We will address the “Prevent Pillar” of the Ending
the HIV Epidemic by using an intersectional lens to address key social and structural determinants of HIV.
Specifically, offering PrEP in the ED will broaden access to this prevention tool to populations experiencing
intersecting vulnerabilities affecting access to health care (e.g., racism, homophobia/transphobia, unstable
housing), as these individuals frequently present in EDs for non-emergent care. The proposed work is framed
by the Consolidated Framework for Implementation Research (CFIR) and addresses early steps in the PrEP
cascade (screening/identification, education/offer of PrEP, PrEP uptake, linkage to primary care). The Specific
Aims are to form and work together with a Community Collaborative to: 1) Use data from 40 interviews we will
conduct with a wide network of stakeholders (ED staff/clinicians and patients, CBO program staff, and ED
administrators that have successfully integrated PrEP in other US hospitals) to identify implementation
strategies to address challenges to offering PrEP in urban EDs in high HIV prevalence settings serving sizable
populations of vulnerable individuals, and 2) Develop a Toolkit of PrEP service delivery implementation
strategies for EDs informed by the Collaborative’s deliberations and review of the stakeholder data. Aims are
informed by pilot interviews with ED leaders in our target counties, who described EDs as appropriate sites to
identify individuals who could benefit from PrEP but do not have access to it. Yet, despite the potential of EDs
to integrate PrEP and promote its uptake, multiple institutional, provider and patient-level challenges need to
be addressed. The Collaborative will work with the investigators to iteratively identify what is known and not
known (in order to guide the stakeholder interviews), draw on data being collected through these interviews,
apply their own knowledge, experience, and expertise, and then formulate a set of strategies to address the
challenges associated with providing PrEP in the ED and linking users to ongoing primary care. The primary
product(s) of the collaborative are a set of ED-based PrEP implementation strategies, tailored to the needs of
individuals with intersecting vulnerabilities. As no single approach will work in all EDs, we will “package” each
strategy, describing its implementation elements (core components, critical resources, staffing, institutional
commitments, protocols/workflows) to create a comprehensive Toolkit from which faciliti...

## Key facts

- **NIH application ID:** 10395102
- **Project number:** 3P30MH043520-33S2
- **Recipient organization:** NEW YORK STATE PSYCHIATRIC INSTITUTE DBA RESEARCH FOUNDATION FOR MENTAL HYGIENE, INC
- **Principal Investigator:** ROBERT H REMIEN
- **Activity code:** P30 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2021
- **Award amount:** $354,248
- **Award type:** 3
- **Project period:** 1987-09-30 → 2023-01-31

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10395102

## Citation

> US National Institutes of Health, RePORTER application 10395102, Designing Differentiated PrEP Service Delivery Models for Implementation in New York City Emergency Departments through a Community Collaborative (3P30MH043520-33S2). Retrieved via AI Analytics 2026-05-26 from https://api.ai-analytics.org/grant/nih/10395102. Licensed CC0.

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