Artificial intelligence (AI) holds transformative potential for public health systems in low- and middle-income countries. The Ghana Health Service (GHS), Ghana's principal public health implementing agency, faces persistent workforce capacity gaps, fragmented digital infrastructure, and nascent data governance frameworks that collectively constrain AI adoption. No systematic review has specifically examined the multi-dimensional organisational and technological readiness of the GHS for AI implementation.
ObjectivesThis systematic review will synthesise evidence on organisational and technological readiness for AI implementation within the GHS and comparable low- and middle-income country contexts, identify barriers and facilitators, document existing AI applications and implementation outcomes, and generate an evidence base to inform national health policy.
Methods and analysisA systematic review will be conducted following PRISMA 2020 guidelines with protocol registration in PROSPERO (CRD420261339477). A Population-Concept-Context (PCC) framework guides eligibility criteria. Searches were conducted across 15 bibliographic and supplementary sources. Two independent reviewers will conduct double-blind screening with inter-rater reliability assessed using Cohen's kappa, targeting a threshold of 0.80 or above as recommended for complex mixed-methods reviews. Quality appraisal will use validated design-specific tools. A convergent integrated mixed-methods synthesis incorporating thematic synthesis and structured narrative synthesis will be applied, with meta-analysis conducted where sufficient quantitative evidence permits. Certainty of evidence will be assessed using GRADE and GRADE-CERQual.
Ethics and disseminationFormal ethical approval is not required as this review analyses existing published evidence. Findings will be submitted for peer-reviewed publication and disseminated to the GHS, Ghana Ministry of Health, and WHO Ghana Country Office.
PROSPERO Registrationcrd.york.ac.uk, identifier CRD420261339477.