# Implementation of a data-driven pre-hospital lay first responder program in Cameroon

> **NIH NIH K01** · UNIVERSITY OF CALIFORNIA LOS ANGELES · 2023 · $191,576

## Abstract

Project Summary/Abstract
Implementing effective prehospital medical care could prevent over half of injury-related deaths. As a first step
toward development of prehospital care systems, several low- and middle-income countries (LMIC) in sub-
Saharan Africa (SSA) have instituted lay first responder (LFR) programs training non-medical professionals
with high exposure to injury in first aid and safe transport of injured patients. Although promising, lack of
research infrastructure and medical records in SSA has limited prior evaluation of the feasibility and
effectiveness of LFR implementation in increasing quality prehospital care. Cameroon is disproportionately
affected by injury and lacks a prehospital care system, likely contributing to treatment delays and preventable
morbidity and mortality. Development of a lay first responder program could increase access to
prehospital care and facilitate timely treatment of injuries but only if it is feasible and effective for the
Cameroonian context. The long-term goal of this research is to reduce the burden associated with injury in
Cameroon. This study’s overall objective is to increase access to quality prehospital trauma care in Cameroon
by using an implementation science approach to develop and evaluate a data-driven LFR program in
Cameroon. The study hypothesis is that is implementation of a data-adapted lay first responder program is a
feasible and effective method of increasing access to prehospital care among injured Cameroonian patients.
To accomplish our objective, this study will pursue three specific aims: 1) Develop a Cameroon-adapted LFR
program using a two-stage, mixed-methods approach; 2) Evaluate feasibility of LFR program implementation in
the Cameroonian context; and 3) Evaluate effectiveness of LFR program implementation in the Cameroonian
context. Validating LFR as a feasible means to increase access to prehospital care will remove a major
roadblock in delivering timely trauma care and provide a critical target for reducing the detrimental impact of
injury on this population. Understanding associations between LFR implementation, physiologic parameters
and outcomes will allow data-informed, iterative improvement of LFR training. Development of a reproducible
method for context-adaptation of LFR could be rapidly scaled for wider implementation throughout Cameroon
and validated in other LMIC contexts and sectors.

## Key facts

- **NIH application ID:** 10805783
- **Project number:** 1K01TW012689-01
- **Recipient organization:** UNIVERSITY OF CALIFORNIA LOS ANGELES
- **Principal Investigator:** Sabrinah Ariane Christie
- **Activity code:** K01 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2023
- **Award amount:** $191,576
- **Award type:** 1
- **Project period:** 2023-09-16 → 2028-08-31

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10805783

## Citation

> US National Institutes of Health, RePORTER application 10805783, Implementation of a data-driven pre-hospital lay first responder program in Cameroon (1K01TW012689-01). Retrieved via AI Analytics 2026-05-25 from https://api.ai-analytics.org/grant/nih/10805783. Licensed CC0.

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