Unlocking the transformative potential of data science in improving maternal, newborn and child health in Africa: a scoping review protocol.

ABSTRACT:

Introduction

Application of data science in maternal, newborn, and child health (MNCH) across Africa is variable with limited documentation. Despite efforts to reduce preventable MNCH morbidity and mortality, progress remains slow. Accurate data are crucial for holding countries accountable for tracking progress towards achieving the Sustainable Development Goal 3 targets on MNCH. Data science can improve data availability, quality, healthcare provision and decision-making for MNCH programmes. We aim to map and synthesise data science use cases in MNCH across Africa.

Methods and analysis

We will develop a conceptual framework encompassing seven domains: (1) infrastructure and systemic challenges, (2) data quality, (3) data governance, regulatory dynamics and policy, (4) tech

SUBMITTER: Akuze J 

PROVIDER: S-EPMC11647284 | biostudies-literature | 2024 Dec

REPOSITORIES: biostudies-literature