THE DYNAMIC PROJECT

A DIGITAL TOOl to improve the management of sick children

The Dynamic Project helps clinical decision making and improves the quality of diagnoses for sick children in Tanzania and Rwanda, thanks to an innovative clinical support algorithm available on a tablet.

Dynamic is a 5-year research project started in 2019 and led by Unisanté’s Digital and Global Health Unit, in collaboration with several partners (see below).

The project is coordinated by Professor Valérie D’Acremont (Principal Investigator) and continues in the footsteps of ALMANACH and e-POCT: it aims at improving healthcare quality for almost 1 million sick children aged 0 to 15, in 140 health facilities through the implementation, the validation and the continuous improvement of e-POCT+, an innovative clinical decision support algorithm (CDSA), combined with point-of-care diagnostic tests. The main goals are to improve the quality of diagnoses, children’s health recovery rates and to reduce the use of antibiotics.

children potentially managed

%

Anticipated Reduction in antibiotic prescriptions

%

Anticipated increase in cure rate

Digital Tools Supporting the Project

The MedAL software suite builds on the validated e-POCT tool

MedAL-creator

medAL-creator
A revolutionary medical ALgorithm creator: clinicians drag and drop the algorithmic logic in a user friendly interface. No coding required at all

medAL-reader

medAL-reader
A tablet-based intuitive consulta-tion guide that helps health care professionals make the best diagnoses and select the best possible treatments and managements

medAL-hub

medAL-hub
A local raspberryPi-based server in the Health Facility allowing tablets to communicate with one another

medAL-data

medAL-data
The medical data always stays in the country. It is collected from the field, cleaned and anonymized on a National dedicated database

medAL-monitor

medAL-monitor helps monitor the medical and operational data

medAL-outbreak

medAL‑outbreak helps spot epidemiological patterns as they happen

medAL-ai

EPFL’s machine learning models analyse the anonymised data to propose algorithm improvements, thus creating a DYNAMIC virtuous circle

 

Medical Algorithms

 

ePOCT + Algorithm

» Simplified ePOCT+ algorithm (draw.io)

» Detailed ePOCT+ algorithm (draw.io)

(Caveat: these representations do not reflect the actual algorithm with 100%
accuracy. The reference algorithm is the ePOCT+ version hosted in medAL-creator.  For the time being, a full access to the platform is required in order to visualize the algorithm. We are working on a better representation)

 

Implementation

 

Project Timeline

stepped-wedge rollout

Tanzania

 

Rwanda

Our Research Partners 

Swiss Tropical and Public Health Institute (Swiss TPH)

Swiss TPH logo

Ifakara Health Institute (IHI)

National Institute for Medical Research (NIMR)

NIMR logo

Ecole Polytechnique Fédérale de Lausanne

Rwanda Biomedical Centre (RBC)

Sponsors

FONDATION BOTNAR

Swiss Agency for Development and Cooperation (SDC)

 

Downloads

SOFTWARE

» Download medAL-reader from the PlayStore

» The rest of the software suite will soon be available on GitHub under the Attribution-NonCommercial-ShareAlike Creative Commons Open Source licence

TALKS & VIDEOS

 

Centre for Primary Care and Public Health
University of Lausanne, Switzerland
Rte de Berne 113
1010 Lausanne
+41 21 314 60 60

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