Bridging Data Fragmentation: A Unified Data Activation Platform for AI-ready Healthcare Systems in Africa

The African healthcare systems are experiencing a nexus of structural limitations: a heavy load of communicable and non-communicable diseases, a lack of financial and human resources, and a strong fragmentation of health data ecosystems. Despite the promising capabilities of artificial intelligence (AI) in enhancing the quality of diagnostics, disease surveillance, and efficiency of health systems, its implementation and expansion in Africa are limited by low data quality, low interoperability, and inadequate governance systems. This paper introduces the African Data Activation System of Health, an integrated, AI-enabled health data activation system that will overcome these underlying obstacles. The study will be conducted with a mixed-methods design, which will combine (I) systematic review of the African health information system implementations, (ii) qualitative thematic synthesis of technical, organisational, and governance challenges, and (iii) quantitative extraction of reported performance indicators of data quality, interoperability and system efficiency. The review evidence will be used to design a cloud-native, microservices-based architecture that can integrate heterogeneous data sources, such as paper-based records, and convert them into analytics-ready datasets by standardising them to HL7 FHIR-compliant formats with the help of AI. AfriDASH uses a probabilistic Master Patient Index, a scalable cloud Lakehouse repository, and built-in governance controls like consent management, privacy-preserving analytics, and role-based access control. The hybrid and federated deployment models allow centralised analytics without violating national and institutional data sovereignty AfriDASH offers a viable and replicable framework of facilitating trustful, fair AI in African health care systems. Although additional empirical research is needed, the platform will overcome technical and socio-organizational obstacles that have hindered the effectiveness of previous digital health efforts. Its effective implementation will rely on the concerted stakeholder action, long-term investment, and intensive implementation research in various African settings.