e-Health toolbox for clinical decision making

e-Health toolbox for clinical decision making

What is this project?

The eHealth toolbox brings together a suite of electronic clinical decision-support algorithms, point-of-care diagnostics, and implementation guidelines. It has been designed with and for use by frontline healthcare workers in resource-limited settings, to reach and diagnose children with fever so as to support informed treatment or triaging decisions.


Why are we working on it?

Every year, millions of children die before their fifth birthday due to treatable conditions including malaria, diarrhoea and pneumonia, largely because the tools available to health professionals for diagnosing and managing childhood illnesses are limited in resource-poor settings.

Diagnostics and medical decision support in these contexts is often limited by funding, low levels of education and poor infrastructure. The remarkable rise of smart mobile devices in recent years offers significant potential for healthcare, but successful integration of this technology into existing infrastructure has frequently proved to be a barrier to implementation. Financial sustainability and scalability are also potential stumbling blocks in low- and middle-income countries.

Engaging end-user communities in the development of eHealth initiatives has proved to be key to successful integration and deployment.


What does it involve?

Work to develop the eHealth toolbox focuses on building evidence for the use of point-of-care diagnostics and electronic clinical decision-support algorithms and capacity among community health workers to use these tools.

Guidance documentation will facilitate development and adoption of these tools. A target product profile for electronic clinical decision-support algorithms is being developed to support uptake of the point-of-care diagnostics, and ensure that R&D and implementation activities are focused on evidence, and designed for the contexts and needs of those who will be using them.

We are also working to build global consensus for these tools, by generating clinical evidence for individual algorithm tools to support care and surveillance. A successful pilot study in Kano State, Nigeria, showed that assessments provided by healthcare workers were of higher quality when they used a validated electronic clinical algorithm. Community health workers were trained to carry out physician-like clinical assessments on children between the ages of 2 months and 5 years presenting at health facilities. They were also trained on the use of malaria rapid diagnostic tests when guided by the algorithm for a febrile case and how to interpret the test results. The data allowed the team, almost in real-time, to see the types of illnesses present in the area, the number of positive malaria cases, and user performance metrics.


What do we expect to achieve?

This work will help to identify baseline criteria for clinical algorithm tools that can improve access to quality care in resource-limited settings, as well as generating data that can inform healthcare system responses.


What is the timescale?

These eHealth toolbox activities are expected to run for 3 years, between 2018 and 2020.


Partners and funding

Assessment of the use of electronic clinical algorithms is being conducted in collaboration with partners including Terre des hommes, THINKMD, and Policlinique Médicale Universitaire. eHealth Africa, THINKMD, and the Kano State Primary Health Care Management Board (KSPHCMB) to implement and assess THINKMD’s eHealth platform, MEDSINC.

This project is supported by Fondation Botnar.


More information

For more information please contact us.

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