Stuart Ssebibubbu, Research Officer, Afya na Haki

Artificial intelligence (AI) integration in healthcare holds immense promise, particularly in sub-Saharan Africa. The healthcare industry is on the brink of a transformative era, thanks to the advent of AI. This shift brings new solutions that have the potential to significantly improve patient care, simplify diagnostics, and enhance treatment procedures. While AI offers great potential for healthcare, it is essential to address the serious concerns about patient privacy and data security. These risks cannot be overlooked. 

Applications and Benefits of AI in Healthcare 

The adoption of AI in healthcare across sub-Saharan Africa is gaining momentum, but it varies significantly across countries and regions due to differences in infrastructure, resources, and expertise. Some African nations are framing national AI strategies to foster AI development and addition in various sectors, including healthcare. For instance, countries such as Kenya, Nigeria, and South Africa have proactively developed policies that support this. 

Tech hubs and innovation centres in countries like Kenya, Nigeria, and South Africa play a crucial role in fostering the growth of AI startups that focus on healthcare solutions. These hubs create vibrant ecosystems, providing resources, mentorship, and funding to support AI innovation in the healthcare sector. In this dynamic landscape, AI-driven health startups like LifeBank in Nigeria and mTIBA in Kenya are leading the change in using AI technologies to tackle critical healthcare challenges. From optimising blood delivery logistics to simplifying mobile health payments, these startups are a testament to the transformative potential of AI in reshaping healthcare delivery across the region. 

AI-powered telemedicine platforms are revolutionising healthcare by breaking down geographical barriers. These platforms, particularly beneficial for underserved and hard-to-reach areas, provide remote consultations and follow-up care. They use AI algorithms to triage patients and efficiently connect them with healthcare service providers. Notably, partnerships like Babylon Health’s collaboration with the Rwandan government are a prime example of how AI-driven healthcare services can be integrated via mobile phones, ensuring accessibility and convenience for patients.

Data monetisation in the health sector in sub-Saharan Africa.

Monetisation converts data into monetary value through selling, sharing, or trading data assets. This practice has gained momentum due to technological advancements and the increasing recognition of data as a valuable resource.

In the realms of health in Sub-Saharan Africa, data monetisation is a complex process that involves leveraging various strategies and technologies to extract value from health-related data. One approach being explored is using non-fungible tokens (NFTs) in healthcare and medical research, allowing patients to monetise their health data and provide valuable information to researchers. Additionally, the value of statistical life (VSL) is vital for monetising health impacts, representing the additional cost individuals are willing to bear to reduce the risk of death.

Data is a crucial resource in big data systems, enabling organisations to extract insights, make informed decisions, and gain a competitive edge in the digital landscape. Big Data Systems (BDSs) are designed to handle massive volumes of heterogeneous data gathered from diverse sources, which are then managed, analysed, and served to end-users and external applications. A framework for end-to-end significant data monetisation has been proposed, outlining the stages of creation, storage, processing, and consumption as integral parts of the monetisation process.

The monetisation of health data goes beyond traditional methods, incorporating personal data for customised advertising and integrating ads in health apps as alternative monetisation strategies. However, this requires balancing technological advancement, ethical principles, and economic strategies to create value for patients and society.

Ethical dilemmas around AI and health data monetisation

One major ethical issue is the potential exploitation of health data for commercial benefit, which may result in inequitable healthcare access and worsen existing healthcare delivery disparities. The monetisation of health data may threaten patient privacy, autonomy, and confidentiality, particularly in regions with weak regulatory frameworks and data protection laws. 

Using AI in healthcare and making money from health data can lead to serious ethical questions. Who owns and controls health information? How do we make sure people agree to their data being used? Can we trust that this data will be handled safely and fairly? There is a risk of hackers stealing health data or AI systems making mistakes that harm people. These are essential problems to solve when turning health data into a business in Africa.

Commercialisation of health data and targeted marketing on platforms 

Commercialising health data and targeted marketing on digital platforms in Sub-Saharan Africa raises significant ethical concerns. The region’s prevalent health issues, such as HIV, cardiovascular disease, low childhood immunisation rates, and diabetes, create a valuable data pool for commercial entities seeking to target specific demographics for advertising. AI-powered algorithms can analyse vast amounts of health data to identify patterns and predict individual health risks. This enables digitally targeted marketing of health insurance products and related services, which has become a prevalent method in recent years. However, using AI in this context raises concerns about personal health data privacy, consent, and the potential for discrimination.

For instance, in healthcare, the targeted advertising of insurance products based on individuals’ health data could lead to discriminatory practices or the exclusion of certain groups from essential services. Exploiting health data for commercial purposes may undermine trust in healthcare systems and data security measures.

While platforms like M-TIBA offer transformative health markets in Africa, presenting affordable solutions to enhance access to healthcare, as described by Al Dahdah in her research. They also raise questions about data security and the potential to exploit vulnerable populations. It is crucial to establish robust ethical frameworks and regulatory measures to protect patients’ rights and ensure equitable access to healthcare in the era of AI and digital health.”

Striking a balance between innovation and patient safety

Technological innovations in healthcare, such as AI, can help doctors share patient information better and work together to provide better health care. However, these advancements must be accompanied by strict privacy measures to safeguard sensitive patient data from breaches and unauthorised access. Healthcare organisations can maintain data integrity while ensuring patient confidentiality by implementing privacy-preserving technologies and encryption methods. 

Healthcare system design should maintain quality care and access to essential health services. Balancing data sharing, research collaboration, and patient-centred care with privacy concerns requires a nuanced approach that considers healthcare innovation’s ethical, legal, and social implications.

A rights-based approach solution

The intersection of AI, health data, and commercialisation raises complex ethical dilemmas that will continue to shape the future of healthcare. As the healthcare industry evolves, it is imperative to adopt a rights-based approach to address the challenges posed by data monetisation and ensure that individuals’ privacy, autonomy, and well-being are protected. A rights-based approach places individuals at the centre of decision-making and prioritises protecting their fundamental rights. In the context of AI and health data, this means ensuring that individuals have control over their personal information, including the right to consent to data collection and use. Sarah Davis advocates for this approach in her work; she often emphasises the need for rights-based approaches to mobile health, ensuring that individuals’ privacy and autonomy are protected, preventing unauthorised access and misuse of their data. Fundamental rights articulated for protection through a rights-based approach include, the right to privacy which includes control of personal information and preventing unauthorised collection, use or disclosure, right to health including access to quality healthcare services plus those enabled by digital technologies, right to equality that ensures that each individual has equal opportunities to benefit from digital health initiatives despite their Socioeconomic status, race, gender or other factors, right to inclusion (non-discrimination) in regards to health status, disability and access to digital technologies and the right to autonomy which includes one making informed decisions on their own health, treatment and the use of digital health tools. 

One of the critical challenges in monetising health data is the potential loss of specificity. When data is aggregated and anonymised, it can become less informative for targeted interventions. This can disproportionately affect structurally marginalised groups, such as racial minorities, who may have unique health needs that are not adequately captured in generalised data sets.

To address this issue, it is essential to consider the ownership of health data and the potential benefits of scientific progress. Individuals should have a say in how their data is used, including the right to share it for research purposes that can advance medical knowledge and improve healthcare outcomes. However, this must be done in a way that protects their privacy and ensures that the benefits of research are distributed equitably.

A rights-based approach demands scrutiny of AI algorithms. Biased data can perpetuate inequality through these algorithms. Thus, we need to rethink, develop, and implement ethical guidelines and strong regulations for AI in healthcare.

Part of the SLSA Blog Series, Exploring the Intersections of Technology, Health, and Law, guest edited by Prof. Sharifah Sekalala and Yureshya Perera. Written as part of the project There is No App for This! Regulating the Migration of Health Data in Africa, funded by the Wellcome Trust (grant number: 224856/Z/21/Z).