Evidence map›Paper›PMID 42375157›Full record

ArticleFrontiers in digital health2026

Assessing organisational and technological readiness for artificial intelligence implementation in the Ghana health service: a systematic review protocol.

Victor Luckyboy Dzramado, Obed Uwumbornyi Lasim, Daniel Owusu-Aboagye

Abstract read
In one paragraph

Article in Frontiers in digital health, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

3 authors.

Victor Luckyboy DzramadoDepartment of Biostatistics, Cape Coast Teaching Hospital, Cape Coast, Ghana.
Obed Uwumbornyi LasimDepartment of Health Services, School of Medical Sciences, University of Cape Coast, Cape Coast, Ghana.
Daniel Owusu-AboagyeDepartment of Community Health, Kwame Nkrumah University of Science and Technology, Kumasi, Ghana.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: 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. Objectives: This 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 analysis: A 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 dissemination: Formal 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 Registration: https://www.crd.york.ac.uk/PROSPERO/view/CRD420261339477, identifier CRD420261339477.

Indexed as

artificial intelligencedigital healtheHealthGhana health servicehealth informaticsimplementation sciencelow-and middle-income countriesorganisational readiness

Identifiers

PMID42375157
PMCPMC13311085

What OpenQuestion holds

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LicenceCC BY
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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.