The lack of adequate and high-quality health data in Africa has impeded the understanding of health-related issues [15]. Several studies have shown that healthcare providers can make informed decisions about the most effective and efficient practices for delivering care to patients by synthesizing available data [16]. In this way, individualized care can be properly designed, adapted, and implemented, and appropriate patient-specific management can be developed to meet the needs of the patient [17, 18]. The availability of health data with algorithms developed from artificial intelligence (AI) and machine learning (ML) can help predict and determine the appropriate diagnosis and prognosis of health conditions, the proper drug prescription, the treatment alternatives, and even strategies to reduce the duration of hospital stays and prevent re-hospitalization and recurrence of diseases [17, 19]. For example, the usage of available health data resulted in a 40 percent reduction in the length of hospital stay and a 50 percent improvement in the effectiveness of treatment elsewhere [20]. Health data in form of patient registries is fundamental to monitoring and evaluating the outcome of clinical treatment and the performance of health technology [21]. These benefits can lead to improved health outcomes and the health status of African patients and the general population.

Africa faces communicable and non-communicable diseases (NCDs), with communicable diseases accounting for the majority of deaths, while NCDs are projected to be the major cause of morbidity and mortality by 2030 [22]. It is pertinent to note that despite the huge burden of diseases, the lack of comprehensive and large-scale health data prevents researchers from understanding patterns in antimicrobial use and resistance to inform clinical decision-making and develop novel therapeutic agents that could reduce the impact of diseases on the continent [15].

Health data helps in the identification of relevant information, opens up new research opportunities and strategies, and creates innovative and cost-effective drugs or interventions for diseases [23]. Moreover, during clinical trials, the response and reaction of different categories of patients to drugs can be predicted with available data, thereby ensuring that approaches to detect the safety and efficacy of drugs are enhanced, and proper comparisons between intervention options are made [17, 23, 24].

The absence of detailed and up-to-date health data has caused obstacles in the management and assessment of healthcare policies, plans, and strategies in Africa [15]. In addition, this data is necessary for the formulation of policies, budgets, and strategies at various levels. Further, through the analysis of collected data, better evaluations, reviews, and modifications of health programs and policies can be made, thereby allowing for more effective monitoring and evaluation [25].

The African Union (AU) estimates that government health spending in Africa accounts for only 1% of total health expenditures, despite accounting for 24% of the global disease burden [13]. Several factors contribute to this, but the lack of precise data makes it difficult for governments and corporate donors to channel their spending on healthcare services. Health data sourcing in Africa has been a challenge due to the lack of a central electronic database and fragmented manual data gathering [26]. As a consequence, this leads to disparities in the collection and capture of inaccurate data, which could lead to the underrepresentation of key segments of an entire population. Since these data are used to develop and validate digital health technologies, data-driven interventions will become detrimental and biased for a particular set of populations [9].

Maintaining patient trust is key to building an efficient healthcare ecosystem. The patient should be assured that their data is safe from phishing, malware attacks, and vulnerability [27]. Until data security is adequately addressed, data collection remains a big problem, and health data poverty will persist. Africa’s growing population presents an opportunity for big data analytics in many business sectors, with healthcare examining the use of big data to find solutions for difficult diseases. Big data analytics requires high-quality internet services for efficient functioning. However, erratic network services pose a threat in that regard, and health data collection becomes a challenge, leading to health data poverty [28].

In Africa, healthcare centers are understaffed and under-equipped with Information Technology (IT) gadgets, patients have limited access to healthcare services, and there are communication gaps between patients and healthcare workers [29, 30]. While the use of mobile phones is only a subset of IT, it is worth noting that due to their low cost, ability to be easily carried around, ease of operation, and the durability of their batteries, particularly in rural areas, where there is unstable power supply, they have enhanced their utilization and penetration in Africa. The developing world has a 79% smartphone penetration rate with 2.2 billion mobile phones as of 2010 [31, 32]. Similarly, 50% of individuals living in rural areas were estimated to have mobile phones in 2012 [33]. The availability and penetration of mobile phones have been explored to minimize health problems and improve healthcare delivery. For instance, a study in Malawi captured the improvements recorded in enhancing healthcare service delivery through real-time information sharing. The approach used Short Message Service (SMS) communication to double enrolment for tuberculosis and HIV treatment [29]. A mobile phone-based system study was conducted in Rwanda, where the pregnancy was monitored through communication to reduce the delay in health-seeking behavior by sending an SMS to healthcare workers alerting them to timely medical support [32]. These initiatives could be expanded to include NCDs and other chronic infections.

Smartphone applications have reduced unnecessary hospitalizations and emergencies, thereby reducing healthcare spending, by encouraging self-management of chronic illness [9]. They have also minimized drug stock-outs by assisting in the procurement, ordering, and monitoring of drugs [33]. Despite the widespread adoption and use of IT in healthcare, these interventions are still relatively small. Lack of access to sophisticated mobile phones, under-skilled healthcare workers, unstable electricity, and the inability to implement large-scale healthcare reforms are some of the problems it faces [34]. There is no doubt that the implementation of IT for aggregating health data in Africa will improve healthcare delivery.

Automation of health data can address the problem of fragmented manual data collection and enhance processes. Healthcare providers and pharmaceutical companies can unlock new insights to help them make better, and more precise judgments. Therefore, this empowers them to respond quickly to life-saving measures. To meet the ever-changing needs of the sector, several activities, including gathering complete patient data, recommending a patient’s unique course of therapy, and giving stakeholders access to clinical data for their evidence synthesis, can be automated [35]. A study conducted in South Africa revealed that several benefits can be derived from the automation of health data in the delivery of healthcare. These include improved information security and patient confidentiality, as well as a reduction in healthcare costs [30].

Healthcare delivery in developing countries is increasingly being delivered through public-private partnerships. Partnerships in some African countries have yielded results and improved data collection. For instance, Program for Appropriate Technology in Health (PATH), a non-profit global health organization, and the Bill and Melinda Gates Foundation partnered with Tanzania, Ethiopia, and Malawi to create a Data Use Partnership [13]. These partnerships provided government agencies and global non-profits with vital data needed to address public health challenges in the region by providing funding for national health information systems [13]. The Gates Foundation’s commitment of about $300 million to facilitate the success of various public health programs in Tanzania would have limited impact without the data obtained through Data Use Partnerships [13]. Thus, private-public partnerships can be leveraged to expand health information gathering and usage across the African continent.

Infrastructure and technology are critical for the collection and utilization of health data in Africa. Adequate infrastructure and technology can improve the quality and accuracy of data, which in turn can inform better decision-making in the health sector. However, there are significant barriers to achieving this in many parts of Africa. A report on the mobile economy in sub-Saharan Africa found that 44% of the adult population is not connected to mobile internet service [36]. This lack of connectivity is a major barrier to the collection and analysis of health data.

This can be done by identifying key infrastructure and providing an alternative to it. For example, the lack of sufficient electric power supply can be tackled by providing solar energy to power the internet service engine.

To improve the collection and analysis of health data for better patient care, the skills, and capacity of healthcare professionals and data analysts need to be enhanced through training, workshops, and educational resources on topics such as data management, analysis and visualization, governance, machine learning, natural language processing, and predictive modeling. Implementing standards and guidelines for data collection and storage can ensure data quality and reliability.

Open data initiatives make health data such as patient records, clinical trial results, and population health statistics available without any restrictions to researchers, healthcare providers, policymakers, and the public, in a format that can be easily accessed and used. This can be achieved through the use of open data portals and APIs. In Africa, open data initiatives can bridge the gap in data availability and accessibility, leading to better health outcomes for all [3].

Promoting a culture of data-driven decision-making in healthcare is important to ensure that health data is used to inform policy and practice. This is achievable using data-driven tools and techniques, developing data literacy, and implementing data governance and management frameworks. Moreover, it can lead to improved patient care and more effective and efficient healthcare systems.