# Improving Performance of a Pediatric TeleMedicine and Medication Delivery Service through mHealth Technology

> **NIH NIH R21** · UNIVERSITY OF FLORIDA · 2023 · $202,378

## Abstract

PROJECT SUMMARY / ABSTRACT
Acute respiratory infection and diarrheal disease are the two leading causes of pediatric death between 1
month and 5 years of age globally. These common problems have low-cost treatments, but these treatments
are most effective when administered early. This is difficult in resource-limited settings, especially at night.
Based on over 5 years of formative NIH-funded implementation science research, our team has built and
deployed a telemedicine and medication delivery service (TMDS) called MotoMeds to improve nighttime
access to care for children. The rationale is that a TMDS generates a multiplier effect to reduce mortality and
morbidity to a greater extent than the provision of in-person emergency medical services (EMS) alone. A
TMDS differs from EMS in that it mobilizes resources from a centralized location and transports these
resources to households. An EMS, on the other hand, identifies patients at households and transports the
patients to centralized resources. EMS logistics, clinical guidelines and decision-support tools do not readily
apply to a TMDS. Novel methods are needed to assure that TMDS models of healthcare delivery safely reach
their potential. MotoMeds was launched in Haiti in 2019 as a pre-pilot focused on safety and logistical
feasibility and configured for scale in a pilot study in 2021. We developed paper-based decision-support tools
for virtual call center exams that were derived from in-person World Health Organization (WHO) guidelines.
Our research exposed a critical need for electronic clinical decision support (eCDS) to assure guideline
adherence at scale and a need to confidently assign triage levels despite limitations in virtual telemedicine
environments. Accurate triage is essential to determine TMDS pathways of care: delivery alone (mild cases),
medication delivery plus an in-person exam (moderate cases) and EMS/hospital referral (severe cases). In the
R21, we will address these needs by concurrently 1) designing an alpha prototype of the eCDS tool through
human centered design followed by qualitative research analysis, while 2) using existing data from our prior
two studies to derive and internally validate a disease severity prediction (DSP) algorithm for integration
into the eCDS tool. In the R33, we will externally validate the accuracy of the DSP and evaluate the
performance of a beta eCDS prototype in a pilot stepped wedge cluster randomized trial. The
performance of the beta eCDS prototype will be determined by comparing rates of guideline adherence
(primary outcome measure) and logistical metrics among providers using paper (control) vs electronic
(intervention) decision support. This single-site pilot will provide essential experience and metrics for a future
multi-site randomized controlled trial of the eCDS integrated with the DSP.

## Key facts

- **NIH application ID:** 10741179
- **Project number:** 1R21TW012332-01A1
- **Recipient organization:** UNIVERSITY OF FLORIDA
- **Principal Investigator:** Eric Jorge Nelson
- **Activity code:** R21 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2023
- **Award amount:** $202,378
- **Award type:** 1
- **Project period:** 2023-08-17 → 2025-05-31

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10741179

## Citation

> US National Institutes of Health, RePORTER application 10741179, Improving Performance of a Pediatric TeleMedicine and Medication Delivery Service through mHealth Technology (1R21TW012332-01A1). Retrieved via AI Analytics 2026-05-25 from https://api.ai-analytics.org/grant/nih/10741179. Licensed CC0.

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