Article
Digital Health and Artificial Intelligence for Strengthening Healthcare Systems in Africa: A Scoping Review
Digital transformation may address persistent constraints in African health systems, but the breadth and maturity of implemented technologies remain unclear. This scoping review mapped empirical evidence on digital health and artificial intelligence (AI) used to strengthen health systems in Africa. PubMed/MEDLINE and Europe PMC were searched from inception to 26 August 2026 using terms for technology, African settings, system functions and implementation. Peer-reviewed empirical studies of an implemented technology and a health-system outcome were eligible. Findings were charted against the World Health Organization health-system building blocks and synthesised descriptively under PRISMA-ScR guidance. Of 1,998 records identified, 1,550 unique records were screened, 61 reports underwent full-text assessment and 58 studies from 20 countries were included. Thirty-three studies (56.9%) were published during 2023–2026. Electronic health records, health-information systems or DHIS2 were addressed in 38 studies and mobile health or short-message services in 27; clinical decision support (n=7), digital surveillance (n=6), telemedicine (n=4) and implemented AI or machine learning (n=2) were less common. Reported contributions included improved access, referral and continuity; more timely and usable data; workforce support; and strengthened clinical processes. Evidence often concerned feasibility, acceptability and scale. Recurrent constraints involved skills and training, equity of digital access, recurrent financing, workflow burden, infrastructure, interoperability and governance. Digital health can support several health-system functions simultaneously, but evidence remains geographically concentrated and dominated by implementation studies rather than robust long-term effectiveness or economic evaluations. Interoperable public infrastructure, sustainable financing, workforce capability, equitable design and accountable AI governance are priorities for responsible scale-up.