The agenda for Universal Health Coverage has driven the exploration of various innovative approaches to expanding health services to the general population (1). This has coincided with the digital revolution of the 90s' which expanded access to Information globally, and Africa has seen a significant adoption of these services especially in the last two decades. Beyond utilization in communication, finances and transportation, public health and healthcare services have seen greater application of these tools to improve population health (2). From disease outbreak monitoring and surveillance, infectious disease contact tracing, telemedicine services, electronic medical records as well as pharmacogenomic applications for medication prescriptions and machine learning for diagnosis and treatment of certain ailments. These tools have contributed to increased access to health services, improved clinical decision making for clinicians, and increased patient engagement and autonomy (3).

Digital health is a general term used to describe the use of internet solutions, big data, and communications technologies to collect, share and manage health information to improve both individual as well as public health (3). Some of the tools include patient-clinician video conferencing tools, sensors for remote monitoring of physical activities, vital signs including EKGs, blood pressures, blood sugar; drone technology for transporting biological products like blood products, vaccines and lifesaving medications to hard to reach locations, electronic dashboard for tracking disease outbreaks, cloud based-databases for storing and retrieval of patient's clinical records, referrals and electronic directories for locating health facilities (4).

Furthermore, the COVID-19 pandemic exacerbated existing health access disparities in the population from low- and middle-income countries revealing gaps in access to care and worse outcomes especially for people of low socioeconomic background (5). This created a call for innovative approach to strengthening the health system, and digital health technology is one of the tools identified for implementation (6). While there is an increased adoption of digital health tools in Africa, digital technology deployed for health care in some instances are siloed from government response leading to fragmentation of services (2).

However, as these tools are beginning to see widespread adoption and use within the health systems, some challenges arise. Firstly, there is no robust evidence suggesting that the widespread use of digital tools strengthens national health systems or makes health care more accessible or affordable. Furthermore, there are concerns that adoption of digital technologies may reveal underlying systemic health systems challenges of infrastructure and workforce gaps in addition to the local, social, political, and economic contexts (2). Moreover, effective adoption of digital technology in health requires presence of robust digital infrastructure like universal reliable broadband access, widespread smartphone ownership and utilization and affordable data access (7). Furthermore, there is a demonstrable digital divide among the public adoption of digital technology, and these mostly follow patterns along age, low socioeconomic status, literacy rates as well as rural vs urban dwellers (8). Herein presents the challenges with implementation of digital health technology within Africa.

As more African countries have adopted digital health tools as part of the strategic approach to expanding health services, there is a need for defining a standard framework for implementation across board (9). This is more important for primary healthcare in the region as it faces many challenges which include inconsistent quality of health care delivered by professionals, and different limitations in accessing relevant diagnosis and treatment. Digital health has been proposed and applied as a tool in solving some of these challenges (10). However, there is a need to understand what works, how best to implement and manage challenges from previous implementations. This review article assesses implementation of digital health solutions for community and primary healthcare workers across the continent to understand and highlight extant challenges, approaches that worked and useful recommendations for future implementations.

In identifying sources for this review, multiple electronic databases were searched. These included MEDLINE via OVID, Embase, Web of Science and CINAHL. The comprehensive search was carried out between 10th and 20th of November 2021 by two authors who retrieved articles published in academic journals, using keywords such as “population health,” “primary health care,” “eHealth,” “mHealth,” “digital health” “Africa” and “low resource setting.” The full search strategy is attached in the Supplementary Material. Abstracts and full-text articles were searched manually in digital sources. Reference harvesting and individual searches for author names were further carried out to identify additional relevant articles. No time limits were applied.

Two authors independently reviewed the abstracts and included original research articles using specified inclusion criteria: original articles written in English, research work related to Africa, literature focused on public/community/population health initiatives and literature focused on health workers in the above contexts. The exclusion criteria were reviews, unpublished manuscripts and research work that focused on clinical use cases without the involvement of community and primary health workers.

An extraction form was prepared and data that was relevant to the study objectives and guided by a recent similar review by Addotey Delove et al. included: author, country, purpose of the study, type of mHealth intervention, health condition, population, type of study, challenges faced, management of these challenges, successes and recommendations made for future implementations and other notes (11).

The original search returned 9,030 articles. Out of these potentially relevant articles, 1,120 studies were excluded because of duplication using a reference manager. Screening the title and abstract of the remaining records for eligibility allowed for the exclusion of further 7,839 records.

This led to a further detailed review of 71 articles for which full-text articles were sought and then reviewed by the authors. Research methods used in the included studies included qualitative studies, surveys, mixed methods, cross sectional studies and cohort studies. The papers reported different applications of mHealth to different health issues and conditions which included maternal and child health (44 studies), infectious diseases (16 studies), health management and cardiovascular health (six studies), ear health and cervical cancer (two studies), and mental health, eye care, logistics (one study each). 15 of the included studies were done in Kenya, 13 in South Africa, 11 in Ghana, 10 in Malawi, six in Uganda, four in Nigeria and Zambia, three in Ethiopia, three in Tanzania, two in Sierra Leone, one in Botswana, Lesotho, and Rwanda.

This review identified public health digital interventions executed in low- and middle-income countries, the implementation approaches, challenges encountered, and made recommendations for future projects. When designed and implemented to meet user needs, the use of mobile health applications could serve as cost effective tools to considerably enhance the administration of public health projects, support community health workers and improve patient outcomes when used as tools for education, disease/compliance monitoring, and for information acquisition (80–82). However, low- and medium-income countries are challenged by unique economic and social disparities such as literacy, lack of infrastructure and effective government policies that pose barriers to implementation, access, and effective utilization of mHealth platforms by patients and healthcare workers (36, 80, 83).

Evidence from the reviewed papers showed that limited internet coverage and poor network connectivity is one of the major barriers facing successful implementation of mHealth innovations in Africa, this is similar to studies conducted in other low and middle income (LMIC) areas like China and India (12, 13, 17, 84, 85). Other barriers such as unavailability, poor accessibility and unreliable power supply are direct symptoms of poor infrastructure and ICT development (20, 22–24, 31, 32, 66, 71). Some of these problems are not peculiar to Africa as they have been reported in Asian and South American countries (86). The development of relevant infrastructure and other ICT systems which are the backbone of mHealth innovations must be addressed to achieve success in the deployment of mHealth innovations (31). Though implementers have devised various means to overcome these barriers such as provision of alternative network providers, using design elements with offline functionalities, provision of solar powered lamps and phone chargers, manual data recording during power outages, etc., these are all temporary solutions which will increase the cost of implementations (13, 20, 23, 31, 43). The overall success of mHealth implementation across Africa will depend on the adequate investment in ICT infrastructure development which will create an environment that will provide the availability and reliability of the internet and electricity supply which will in turn ensure subsequent successful implementation of mHealth innovations.

Digital illiteracy is another barrier that impairs successful implementation of mHealth innovation in Africa, this problem has also been found in implementations in other LMICs (27, 87). These challenges are more evident in the rural than urban regions. According to Kallander et al., some of the major considerations for successful implementations are collaboration, literacy, culutre and partnerships (88). Improvement in digital literacy specifically in rural regions and generally across Africa can be achieved by bringing together major stakeholders via multisectoral and multidisciplinary collaborations. These stakeholders could create training and mentorship programs and ensure provision from both government and non-governmental organizations contributions to special funding pools for mHealth projects to boost the uptake of mHealth innovations and improve the efficiency of mHealth implementations (20, 23, 25, 33, 37–40, 84). Lastly, to address product design challenges causing technical difficulties during implementations, developers should ensure that mHealth applications could be integrated with the current facility-level electronic health information system while they empower the local team to be able to provide routine technical support in order to create a self-sustaining mHealth system model (35).

This review highlights key challenges inherent in implementation of digital health solutions in low-and-medium income countries in sub-Saharan Africa. These include limited coverage and network connectivity, lack of technological competence, lack of power supply, limited mobile phone usage and application design challenges. Despite these challenges, this review suggests that mHealth solutions could attain effective usage when healthcare workers receive adequate onsite training, deploying applications designed in an intuitive and easy to understand approach in a manner that fits into the users existing workflows, and involvement of the stakeholders at all levels in the design, planning, and implementation stages of the interventions. Although there is need for further research to establish the direct impact of mHealth tools on clinical outcomes and to generate best practice frameworks for implementation, this paper reveals the importance of larger investments of time, resources, and policies to support the development of infrastructures that can enhance the uptake and effectiveness of digital healthcare solutions in sub-Saharan Africa.

This study is limited by the exclusion of studies not done in English language, which would have limited the number and scope of studies found. Also, most resources were from the peer-reviewed literature, which would lead to the exclusion of a lot of other mHealth implementations that might exist in reports and other gray literature resources.

AO, JO, and CAz contributed to all aspects of the article. RI conducted the search with AO and edited different aspects of the article. BN, CAk, GB, AA, EN, TB, AE, DI-O, and SO worked on the knowledge synthesis and contributed to editing and proofreading the article. AE, DI-O, and SO worked on the discussion and conclusion aspects of the article. All authors contributed to the article and approved the submitted version.

JO is presently employed by the Kosofe Local Government, Lagos, Nigeria. CAk is presently employed by The Neo Child Initiative, Nigeria. DI-O is presently employed by CareMonie Health Financing, Nigeria. The remaining authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article, or claim that may be made by its manufacturer, is not guaranteed or endorsed by the publisher.