HPSR3-AUTOMATE - Harnessing routinely collected data for timely healthcare decisions in LMICs amidst pandemics

About this project

The emergent and re-emergent of global pandemics present significant challenges in low-and-middle-income countries (LMICs) where health systems have limited capacity for timely identification and monitoring of the potential impact of pandemics. This project aims to strengthen health systems in LMICs via digitalisation to improve preparedness and responsiveness to pandemics. It has three interrelated workstreams: an assessment of current capacity to use routinely collected data for healthcare decisions, including an illustrative analysis to showcase use of data to inform policy/practice; co-development and implementation of digital health and data analytics/visualization tools and processes to facilitate data access and use for timely decisions; and piloting and evaluating feasibility/process of digitalization of healthcare data. The project is jointly led by two partners in Kenya and the UK: the Tropical Institute of Community Health and Development in Africa (TICH) in Kenya and Keele University - UK, in collaboration with Kenyan Ministry of Health and the University of Sunderland - UK. It is a three-year project, starting November 2024, being implemented in two counties of western Kenya: Kisumu and Siaya. Findings will inform the development of appropriate data digitalization and visualization/analytics tools to enhance evidence-based decision making for improved performance of the health systems with feedback loops at all levels. Potential impact extends beyond the study s…

Published by

Keele University · Academic, training and research

Countries

Kenya

Sectors

Health statistics and data

Funded by

Department of Health and Social Care

Implemented by

Tropical Institute of Community Health and Development, University of Sunderland

Published by Keele University to the International Aid Transparency Initiative (IATI), last updated 30 Jun 2025 and imported automatically. IATI identifier: GB-COH-RC000655-AUTOMATE-502851.

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