# Development of clinical decision tools for management of diarrhea of children in high and low resource settings

> **NIH NIH R01** · UTAH STATE HIGHER EDUCATION SYSTEM--UNIVERSITY OF UTAH · 2024 · $443,937

## Abstract

Abstract
Diarrheal diseases are the among the leading cause of death in children worldwide, most of which occur in
low-income countries. In high-income countries, pediatric diarrhea remains a major utilization of healthcare
resources. The cornerstone for management of diarrhea is rehydration, though antimicrobials are beneficial in
some instances. Unfortunately, given that treatment is frequently empiric, based mostly on clinical suspicion for
bacterial causes, antimicrobials are overused in management of diarrheal illness worldwide. In high-income
countries, diagnostic testing is oftentimes overutilized. Thus, there is a need for clinical decision support tools
for antimicrobial and diagnostic stewardship in many settings. Current clinical prediction tools are based mostly
on patient-intrinsic properties such as the clinical exam and symptom history specific for that patient. We have
preliminary data suggesting that the integration of patient-extrinsic data, including climate and seasonality
parameters, and population-level pre-test probabilities (from prior patients and prior years’ prevalence), can
improve the performance of a clinical prediction model. We also have preliminary data showing the potential for
an electronic clinical decision-support tool (eCDST) that estimates diarrheal etiology to decrease antibiotic
prescription rates. Our overarching goal is to: 1) improve diarrhea clinical prediction through integration of
patient-extrinsic data sources, and 2) explore the potential feasibility and utility of an eCDST, such as a
smartphone application or an electronic health record tool. In Aim 1, we will use data from several prospective
clinical studies of pediatric diarrhea to build improved clinical prediction models that includes patient-extrinsic
data sources. In Aim 2, we will determine the potential feasibility, utility, and economic impact of an eCDST for
antibiotic and diagnostic stewardship by examining clinican and caregiver perspectives through in-depth
interviews and focus groups. We will also perform an economic evaluation of eCDST in a US setting.
Completion of the Aims will result in an optimized clinical prediction model using big data and lay the
groundwork needed to inform the design of implementation studies of eCDSTs for management of pediatric
diarrhea.

## Key facts

- **NIH application ID:** 10855765
- **Project number:** 5R01AI135114-07
- **Recipient organization:** UTAH STATE HIGHER EDUCATION SYSTEM--UNIVERSITY OF UTAH
- **Principal Investigator:** Daniel Ted Leung
- **Activity code:** R01 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2024
- **Award amount:** $443,937
- **Award type:** 5
- **Project period:** 2018-05-08 → 2025-05-31

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10855765

## Citation

> US National Institutes of Health, RePORTER application 10855765, Development of clinical decision tools for management of diarrhea of children in high and low resource settings (5R01AI135114-07). Retrieved via AI Analytics 2026-05-25 from https://api.ai-analytics.org/grant/nih/10855765. Licensed CC0.

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