Towards data-driven models for diverging emerging technologies for maternal, neonatal and child health services in Sub-Saharan Africa: a systematic review

Abstract

Sub-Saharan Africa (SSA) has the highest maternal and under-five mortality rates in the world. The advent of the coronavirus disease 2019 exacerbated the region's problems by overwhelming the health systems and affecting access to healthcare through travel restrictions and rechanelling of resources towards the containment of the pandemic. The region failed to achieve the Millenium Development Goals on maternal and child mortalities, and is poised to fail to achieve the same goals in the Sustainable Development Goals. To improve on the maternal and child health outcomes, many SSA countries introduced digital technologies for educating pregnant and nursing women, making doctors’ appointments and sending reminders to mothers and expectant mothers, as well as capturing information about patients and their illnesses. However, the collected epidemiological data are not being utilised to inform patient care and improve on the quality, efficiency and access to maternal, neonatal and child health (MNCH) care. To the researchers’ best knowledge, no review paper has been published that focuses on digital health for MNCH care in SSA and proposes data-driven approaches to the same. Therefore, this study sought to: (1) identify digital systems for MNCH in SSA; (2) identify the applicability and weaknesses of the digital MNCH systems in SSA; and (3) propose a data-driven model for diverging emerging technologies into MNCH services in SSA to make better use of data to improve MNCH care coverage, efficiency and quality. The PRISMA methodology was used in this study. The study revealed that there are no data-driven models for monitoring pregnant women and under-five children in Sub-Saharan Africa, with the available digital health technologies mainly based on SMS and websites. Thus, the current digital health systems in SSA do not support real-time, ubiquitous, pervasive and data-driven healthcare. Their main applicability is in non-real-time pregnancy monitoring, education and information dissemination. Unless new and more effective approaches are implemented, SSA might remain with the highest and unacceptable maternal and under-five mortality rates globally. The study proposes feasible emerging technologies that can be used to provide data-driven healthcare for MNCH in SSA, and the recommendations on how to make the transition successful as well as the lessons learn from other regions.