Development of digital decision-support tools to improve rehydration and antibiotic guideline adherence for diarrhoeal diseases

Case management Bangladesh - Mali - Haiti completed

Project timeline: 01/01/2014 - 31/03/2022

Lead Researcher

Dr. Eric Nelson

Organisation / Institution

University of Florida


NIH - National Institutes of Health

Project summary

For over ten years, we have sought how best to develop decision-support tools for clinicians treating diarrhoeal disease. This is important because of a need to rapidly train large numbers of providers during cholera outbreaks, rapidly re-educate when guidelines change, address inappropriate antibiotic use, and allow for differences in epidemiology by season and place. We have built tools in both paper and digital formats, and evaluated their impact in clinical trials. Now, we are collaboratively building digital tools that depend on models developed through machine learning. In a large international collaboration, we have built and evaluated improved algorithms to assess dehydration for children and adults (project led by A. Levine at Brown University) and provide a probability that a patient has only a viral disease based on real-time weather, clinical and epidemiologic data (project led by D. Leung at Utah University). In addition to helping to improve cholera response, these tools represent a significant shift in how clinical decision-support might be in 10 years.

Potential for public health impact or global health decision-making

The impact of this research is to first improve rehydration and antibiotic guideline adherence. Secondly, the impact is to make possible dynamic decision-support that is responsive to where and when the patient is being treated.


Daniel Leung, University of Florida
Adam Levine, Brown University
Ashraful Khan, icddr,b
Adama Mamby Keita, Mali
Dr. Md. Nur Haque Alam, icddr,b

Key Collaborators

Brown University
Utah University
International Centre for Diarrhoeal Disease Research, Bangladesh

Resources (6)


Derivation of the first clinical diagnostic models for dehydration severity in patients over five years with acute diarrhea


A modular approach to integrating multiple data sources into real-time clinical prediction for pediatric diarrhea


Clinical predictors for etiology of acute diarrhea in children in resource-limited settings


Ethnographic exploration of diarrheal disease management in public hospitals in Bangladesh: from problems to solutions


Electronic decision support and diarrhoeal disease guideline adherence (mHDM): a cluster randomised controlled trial


Evaluation of a smartphone decision-support tool for diarrheal disease management in a resource-limited setting