Reviewnpj health systems2025
Enabling data-driven decision-making for innovative health care and delivery in Africa.
Review in npj health systems, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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.
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.
Who cites it
0 citing papers in PubMed.
No citing paper in PubMed yet.
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
9 authors.
Funding
Abstract
The information age, fueled by globalization and technological advancements, has transformed the data landscape, impacting decision-making, management, governance, and policy intervention across various sectors. The health sectors are no exception, experiencing a data explosion driven by ongoing research initiatives and advancements. This transformation necessitates a shift towards evidence-based practices, emphasizing the importance of high-quality, timely, accessible data at all levels. Data science offers a compelling solution, particularly in Africa, where resource scarcity demands prudent allocation. By leveraging the abundance and diversity of data, data-driven decision-making and policymaking can be fostered. This approach holds immense potential to develop accurate, effective, measurable policies, addressing Africa's healthcare challenges. In this paper, we delve into the need for leveraging data on health decision-making and policy implementation in Africa. We further explore the intricate relationship between the burgeoning field of data science, Africa's persistent infrastructural deficiencies, and the continent's ongoing healthcare transformation challenges. We use available data, publications, and information resources across Africa to highlight the challenges, and opportunities and provide a roadmap and recommendation involving data-driven and policy-making decisions in the healthcare sector. We conclude by making proposals, and recommendations, and advocating for global and local approaches to data sharing and capacity-building initiatives by policymakers in collaboration with researchers to foster a system of data-driven decisions in health care. We emphasize the need for data-sharing partnership model, turning African biomedical data into treasures and valuable assets, and have highlighted different data elements that can contribute to data-driven decisions in healthcare.
Identifiers
What OpenQuestion holds
Registered trials
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.