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Abstract
Objective The increasing burden of hypertension in Africa underscores the need to embrace digital health innovations to improve delivery and access to quality hypertension care. This review aimed at (1) identifying barriers and facilitators to the implementation and uptake of digital health tools and (2) examining the scope and use of digital health tools based on the Practical Reviews in Self-Management Support (PRISMS) taxonomy.
Materials and methods We searched PubMed, CINAHL (Medline) and HINARI from inception to June 2024. The Joanna Briggs Institute (Population, Concept, and Context (PCC)) framework guided the formulation of research questions, and the PRISMS taxonomy was used to analyse the functions of digital tools.
Results Sixteen studies (k=16) across three African regions were included. Common digital health tools were mobile Health (mHealth) or electronic Health applications and short message service (SMS)-based interventions. Supported self-management functions included medication adherence (k=10), lifestyle counselling (k=12) and home blood pressure monitoring (k=9). Implementation strategies included prior training (k=10), continuous digital support (k=10) and provision of resources including BP devices and data credit (k=11). Targeted users were healthcare workers (k=8), patients (k=11) or both (k=3). Barriers included limited digital literacy, poor communication among healthcare workers, privacy concerns and weak internet infrastructure. Facilitators included competency-based training, contextual adaptations, continuous technical support and enhanced user experience through effective feedback systems between users.
Conclusion Digital health tools, particularly mHealth apps and SMS, support key hypertension self-management tasks in African settings. Addressing technological and contextual barriers while reinforcing training and support systems is critical to successful implementation and scale-up.
Introduction
Hypertension is the leading risk factor for cardiovascular disease (CVD) globally.1 It is estimated that about 1.28 billion people worldwide live with hypertension.1 In 2019, hypertension accounted for 7.9 million deaths among adults between the ages of 30 and 79 years.2 Additionally, the recent global hypertension report estimates the burden of hypertension in Africa to be 36%.3 Consequently, most CVD-related deaths occur in low–middle-income countries (LMICs) including Africa. Of note is the increasing burden of hypertension even among populations with other conditions, particularly diabetes in Africa.4 Indeed, hypertension is a major public health problem in Africa, which is partly explained by the rising spate of urbanisation that shapes societal behaviours and mode of life of populations. Without robust and coordinated response mechanisms, the burden of hypertension may worsen, and derail efforts towards the United Nations’ sustainable development goal of reducing premature CVD mortality by 25%.5
Across health systems in Africa, the essential health workforce required for managing hypertension continues to dwindle due to poor conditions of service, which drives the migration of health workers from low-resource settings to high-income settings.6 It is estimated that even at three clinical visits per year, most health systems in LMICs, including Africa cannot meet the needs of patients with hypertension.7 Moreover, limited access to healthcare, space at health facilities and inadequate provider–patient interactions are documented barriers to hypertension control in Africa.8 9
However, the advent of digital health tools in addition to innovative models like team-based care offers a promising alternative approach to bridging the physician–patient gap in hypertension care and empowe patients to actively engage in care decisions.10 In line with the conceptualisation and application of digital health tools in hypertension management by the American Medical Association, digital health tools consist of a broad scope of tools used to engage patients for clinical purposes; collect, organise, interpret and use clinical data; manage outcomes and other measures of care quality (online supplemental table 1).11 Digital health tools may include electronic Health (eHealth) and mobile Health (mHealth), telemedicine and other remote monitoring systems including smart wearables devices used for tracking daily activities.12 These platforms are applied to capture remote data and facilitate the transmission of information across the healthcare system.
Although digital health tools have been widely implemented in the management of hypertension in developed countries, their adoption is still evolving in Africa. Given the increasing demand for hypertension care in Africa coupled with the shortage of healthcare workers, blood pressure control may continue to be suboptimal without effective care strategies.13
This review aims to identify contextual factors affecting the adoption of digital health tools and describe their utility in hypertension care in Africa.
Materials and methods
This scoping review followed the Preferred Reporting Items for scoping Reviews and Meta-Analyses extension for scoping reviews. We adopted a scoping review design instead of a systematic review to enable a comprehensive exploration of diverse and emerging digital health tools, which may be applied in different ways in hypertension care in Africa.
Protocol registration
Not registered.
Eligibility criteria
Inclusion: the current scoping review included peer-reviewed articles that reported on (1) use of digital health tools published in English, (2) among patients diagnosed with hypertension and their caregivers, healthcare workers involved in hypertension care or programme implementors in African context; (4) published in English from the inception of included databases until June 2024; and (v) African context. Exclusion: (i) non-hypertension-related interventions, (ii) non-primary study designs (eg, abstracts, policy papers, commentaries, reviews).
Derivation of search terms
In line with the JBI methodological framework for conducting scoping reviews, the concepts of PCC (P=Population, C=Concept, and C=Context) were adopted. Three electronic databases were searched: CINAHL, PubMed and HINARI. The search strategy was first developed for PubMed and adopted for other electronic databases (online supplemental table 2).
Selection and screening of studies
Search results from each database were transferred to the Endnote platform to identify and eliminate any duplicate entries. Citations were imported into Covidence for titles and abstract screening. Two reviewers independently conducted title and abstract screening, and disagreements were resolved by CO (author) by consensus.
Data charting
The data extraction sheet was created and reviewed, with all data charting activities completed and subsequently verified. Alongside the main findings reported by authors, observations from programme implementation documented in supplementary materials or the limitations sections of articles were also extracted.
The modified Practical Reviews in Self-Management Support (PRISMS) taxonomy was adopted to collect relevant information about the features of digital health tools.14 The PRISMS taxonomy consists of 14-item components that support the self-management of people with long-term conditions or their caregivers. These components include information about the condition, provision of equipment and social support. Other aspects include how support is delivered, who provides it, what the support focuses on, duration of intervention and sustainability actions.
Collating, summarising and reporting the results
Data were initially extracted and categorised as barriers or facilitators based on the percentage of studies reporting each barrier or facilitator. Items were then coded according to predominant constructs, and themes were identified and validated by a second reviewer (online supplemental tables 3 and 4). Barriers were assigned negative (−) barriers and positive (+) for facilitators. Common themes were assigned with distinct colours and then displayed under the main concept of the PRISMS taxonomy. The identified barriers and facilitators were disaggregated and stratified at policy, organisation, community and end-user levels to highlight gaps and key considerations for the effective implementation of multilevel digital health innovations in hypertension care in Africa.
Conclusion
In conclusion, this review examines the factors influencing the adoption of digital health tools in hypertension management in Africa. A high level of agreement emerged between healthcare workers and patients regarding the key barriers and facilitators, underscoring the importance of multistakeholder engagement in enhancing uptake. To support successful implementation, it is essential to garner input and support from political, community and organisational levels in the development of user-friendly digital tools that integrate seamlessly into clinical workflows, strengthen provider–patient relationships and ensure interoperability with existing health information systems. Future research should focus on evaluating implementation strategies, user experiences and long-term outcomes of digital health interventions in real-world hypertension care settings across diverse African contexts.
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