TY - JOUR
T1 - Enabling data-driven decision-making for innovative health care and delivery in Africa
AU - Agamah, Francis E.
AU - Anyanful, Akwasi
AU - Ryabinina, Oksana
AU - Twum, Joel
AU - Tunga, Mahadia
AU - Skelton, Michelle
AU - Bope, Christian D.
AU - Chimusa, Emile R.
AU - Thomford, Nicholas E.
PY - 2025/12/16
Y1 - 2025/12/16
N2 - 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.
AB - 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.
KW - health care
KW - health occupations
U2 - 10.1038/s44401-025-00047-y
DO - 10.1038/s44401-025-00047-y
M3 - Article
SN - 3005-1959
VL - 2
JO - npj Health Systems
JF - npj Health Systems
IS - 1
M1 - 48
ER -