A systematic review: Evaluating the implementation determinants and progress of artificial intelligence, big data,...

East African health systems face dual challenges of infectious disease burdens and rising non-communicable diseases within resource-constrained environments. Artificial Intelligence (AI), Big Data, and Cloud Computing offer transformative potential for healthcare delivery through enhanced diagnostics, optimized resource allocation, and improved care continuity.

We conducted a systematic review following PRISMA 2020 guidelines, searching PubMed, IEEE Xplore Web of Science, and Google Scholar for studies on AI, Big Data, and Cloud Computing applications in East-African healthcare systems (2014-2024). Risk of bias was assessed using the ROBIS-I tool, with narrative synthesis used to analyze findings. Thematic analysis was guided by the Consolidated Framework for Implementation Research (CFIR).

From 129 identified studies, 19 met inclusion criteria. Findings revealed promising pilot implementations demonstrating preliminary evidence of improved diagnostic accuracy and operational efficiency. However, based on the available evidence, no interventions achieved sustainable scale-up using predefined scaling criteria. Five key barriers emerged: inadequate infrastructure (reported in 74% of studies), limited workforce digital literacy (58%), incomplete governance frameworks (47%), poor system interoperability (42%), and unsustainable financing models dependent on donor funding (37%).

A significant policy-practice gap exists between comprehensive national digital health strategies and ground-level implementation. While pilot projects show measurable benefits, systematic barriers prevent scaling to routine practice. Based on the available evidence, success may require coordinated investments across infrastructure, workforce development, governance, interoperability, and sustainable financing, supported by implementation science approaches. However, the moderate risk of bias in included studies and the developing state of implementation research in the region warrant cautious interpretation of these findings.