# Pediatric Transport Learning Laboratory

> **NIH AHRQ R18** · UNIVERSITY OF WASHINGTON · 2024 · $499,858

## Abstract

Project Summary/Abstract
The overall goal of this project is to advance the care of pediatric patients (up to 21 years of age) during
medical ground or air transport from one hospital to another within a regional network. The project will build on
our previous experience with neonatal patient transport and use a five-stage innovation cycle, including:
problem analysis, design, development, implementation, and evaluation to identify and address the salient
issues and risks of regional neonatal transportation for which new and innovative approaches are needed.
In collaboration with transport providers and other stakeholders, we will analyze current workflow processes,
transport records (local and statewide databases), and facilities at referral and receiving facilities to develop a
complete understanding of system issues and to define the current and ideal states. This detailed problem
analysis phase will enable the integration of real-time data into a transport “digital twin” model to optimize
regional consultation, triage, and transport of pediatric patients to facilities with the appropriate level of care
and availability of space and staffing.
With the input of clinical transport team staff and stakeholders, the project team will work with collaborators
from the University of Washington Industrial and Systems Engineering Department to integrate machine
learning into the Transport Monitoring and Communications (T-MAC) system to support the analysis of data
feeds while on transport. The machine learning augmented T-MAC system will undergo repeated testing and
revision to ensure that it can functionally and efficiently facilitate information flow between the medical control
physician, referring facility and transport team.
In addition, we will develop robust processes to support information flow to patients and families in the peri-
transport period. To accomplish this, we will work with families to identify gaps in communication and
connection to local and receiving facility resources and identify transport-specific needs.
The efficacy of the T-MAC system will be evaluated in a realistic in situ simulation and clinical settings. We are
confident that the lessons learned through this study will improve pediatric patient safety on medical transports
and will be transferable to patient populations that undergo both short and long-range interfacility transports.

## Key facts

- **NIH application ID:** 10916458
- **Project number:** 5R18HS029607-02
- **Recipient organization:** UNIVERSITY OF WASHINGTON
- **Principal Investigator:** Rachel A Umoren
- **Activity code:** R18 (R01, R21, SBIR, etc.)
- **Funding institute:** AHRQ
- **Fiscal year:** 2024
- **Award amount:** $499,858
- **Award type:** 5
- **Project period:** 2023-09-01 → 2027-06-30

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10916458

## Citation

> US National Institutes of Health, RePORTER application 10916458, Pediatric Transport Learning Laboratory (5R18HS029607-02). Retrieved via AI Analytics 2026-05-26 from https://api.ai-analytics.org/grant/nih/10916458. Licensed CC0.

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