2. Datafication infrastructures

Health insurers’ reliance on data analytics is part of a broader economic transformation in managing business processes, using digital technologies to achieve a competitive advantage. Data analytics involves the conversion of human activities into digital data points, which can be continuously tracked and analysed for insights and oriented at influencing future decision-making and behaviours to generate certain forms of value. The process of transforming human life into data as quantified social insights and meanings – predominantly to generate economic value – is called datafication (Mejias and Couldry Reference Mejias and Couldry2019; Taylor and Broeders Reference Taylor and Broeders2015). Structurally, datafication relies on multi-layered physical and non-physical infrastructures such as software, hardware, platforms and networks for data surveillance, analysis, storage, transfer and monetisation (Mejias and Couldry Reference Mejias and Couldry2019). Datafication has the potential to create benefits through increased innovation and efficiency in service delivery. In health, datafication involves the process of converting certain aspects of an individual’s and society’s health and well-being into digital data, often collected through digital technologies such as mobile applications, wearable technologies and electronic health records.

Increased datafied health practices have exposed social justice concerns about the potential to entrench inequalities, due to the power asymmetries that exist in the way data is collected, positioned, analysed and turned into knowledge and value (Dencik et al. Reference Dencik, Jansen and Metcalfe2018). This is, for instance, through Electronic Medical Records (EMRs), which offer a real-time clinician-focused account of a patient’s data, diagnosis and treatment within a healthcare practice and are used to support other processes such as billing, quality management and surveillance (World Health Organization 2012). Electronic Health Records (EHRs), which offer a comprehensive longitudinal account of a patient’s medical history, diagnoses and treatments across different encounters with healthcare providers (World Health Organization 2012), also have the potential to expose patients to vulnerability for parts of the population who have lower health outcomes and may be seen as more risky to insure and treat. EMRs and EHRs have redefined patient identity and experience through data constructs that have broadened the narrow clinician-patient relationship to include vendors of health technologies, making the body both a subject of care and an object of data production. At the business level, datafication has created unique opportunities for collaboration between public health institutions and data corporations, creating new pathways for patient data to be (re)used, (re)produced and (re)situated.

Health data is increasingly treated as a capital input, valued for its potential to drive technological innovation and economic growth within health markets, rather than primarily serving social or ethical objectives. As digital data is neither neutral nor natural, but a product of human decisions shaped by politics, economics and culture, we can also analyse the often invisible aspects of power produced through quantification. For instance, the use of datafication technologies such as AI in healthcare settings has been proven to lead to poor quality or denial of care due to algorithmic biases, especially for vulnerable patients (Redden et al. Reference Redden, Brand and Terzieva2020). Datafication of health has also led to excessive data bureaucracies and ‘meaningless work’ for healthcare staff that shifts clinical priorities away from patient care (Hoeyer and Wadmann Reference Hoeyer and Wadmann2020).

Codification of human life into data realities for real-time and predictive use raises questions about who and what the data infrastructural agents, subjects, objects and beneficiaries are (Mejias and Couldry Reference Mejias and Couldry2019). Within health, datafication is seen as a means to improve efficiencies and support cost-effective healthcare decisions by enabling analysis of large datasets, optimising resource allocation, and streamlining clinical workflows. With tech corporations accruing significant influence in health through the provision of infrastructures from software, data storage and analysis, this economic framing of data has created new forms of dependency relationships, with governments’ responsibility to health provision being increasingly handed over to private corporations (Maschewski and Nosthoff Reference Maschewski and Nosthoff2022).

In the provision of health insurance, particularly, digital technologies invisibilise the rationalities behind actuarial practices. Actuarial practice is the application of mathematical and statistical methods to assess, predict and solve financial risks, particularly in the insurance context (Espinosa et al. Reference Espinosa, Drummond, Russo, Williams and Wix2025). Within health, the transformation of various aspects of health and behaviour into quantifiable data has enabled actuaries to perform granular and personalised risk calculations and predictions. This creates far-reaching consequences for how an economy of moral judgement by private corporations is normalised and solidified for invasive access to health data (Kiviat Reference Kiviat2019; Sadowski et al. Reference Sadowski, Lewis and Bednarz2024). The increased datafication of actuarial practices has also been linked to algorithmic biases and discrimination (Eubanks Reference Eubanks2018; Herzog Reference Herzog2021). Over time, actuarial practices have made it possible to perform ‘precise’ and targeted behavioural alterations and predictions, based on increasing cost efficiencies and lowering future risk. This is particulary problematic in post-colonial states, especially those with histories of racial division, where race remains central to the articulations of risk and exposure. Unlike the past, when the risk calculation model relied on a more analogous approach of filling in surveys, questionnaires, and secondary forms of data, digital technologies make it possible to extend the forms of stratification based on dispassionate digital health data, at speed and scale.

3. Law, risk and coloniality in the South African context

The present-day realities of an inadequate public healthcare system and financing in the South African context can be traced to the apartheid system of racial classification and segregation, which institutionalised a legal framework of discrimination and victimisation of non-White citizens in all areas of social and economic life. During this period, health systems became an instrument for furthering the agenda of the apartheid state. Health policies in apartheid South Africa were geared towards advancing increased public expenditure on health services in favour of the White population while providing limited services to non-Whites (Maphumulo and Bhengu Reference Maphumulo and Bhengu2019), mainly based on maintaining the reproduction of labour for economic enterprises. The concern for labour led to increased spending on health services for urban-based Blacks as compared to those living in the Bantustans (homelands)Footnote ¹ (Price Reference Price1986). In the Bantustans, the apartheid health policies served to maintain relations of dependence on the apartheid government for financing, which could then be used as leverage for sustaining racial segregation through the ‘independence’ of the homelands while legitimising inequality (Whyle and Olivier Reference Whyle and Olivier2023).

Apartheid policies also led to the growth of private healthcare, which catered exclusively to White South Africans, with 80% having access to private health insurance in the 1960s to 1970s (Susser Reference Susser1983). The end of the apartheid system led to neoliberal reforms, which saw the deregulation of medical schemes, relaxation of licensing requirements for private healthcare facilities, and increased privatisation aimed at racially expanding medical scheme membership. Shifting economic responsibility for healthcare provision onto the private sector replaced unpopular segregation policies with economic discrimination, in an attempt to mitigate rising Black opposition with the inclusion of Black elites into high-quality private care, while the majority continued to rely on the government (Naylor Reference Naylor1988; Price Reference Price1986; Whyle and Olivier Reference Whyle and Olivier2023).

4. Entrenching market provisions in the post-colonial era

The African National Congress (ANC), which came into power in 1994, included an agenda for a UHC-system reform in the 1955 Freedom Charter. However, the radical redistribution principles embedded in the Charter’s nationalist economic and socialist ideologies were abandoned in favour of a Washington Consensus-based neoliberal economic plan: Growth, Employment, and Redistribution (GEAR). GEAR significantly influenced health policy reforms by limiting healthcare spending and discouraging the regulation of private health service providers, including insurance providers (Baker Reference Baker2010). The shift towards neoliberalism was facilitated by a political pact between Black elites and White capital in a new state that enshrined property rights and prioritised orthodox development economics marked by market-driven solutions (Baker Reference Baker2010; Bond Reference Bond2000). Without challenging the capitalist structural economic interests, the idea of an African economic renaissance as reformation was symbolic, advancing a small new class of African bourgeoisie, while reinforcing historical inequalities (see Nkrumah Reference Nkrumah1965).

The post-apartheid period led to notable health equity improvements, such as increased universal funding for primary healthcare services and a more representative healthcare workforce. However, such gains were outweighed by racialised health inequalities, due to restricted government public health spending (Mayosi Reference Mayosi and Benatar2014). In part, this inequality was due to the ANC’s trade-offs at the end of apartheid – pushing for broad redistribution, without necessarily dismantling or destabilising colonial structures, such as private insurance. The South African story is consistent with other post-colonial states, which failed to usher in radical transformation and significant improvements in the material conditions of populations. In keeping with the World Bank’s neoliberal agenda, post-colonial countries saw a reduction in government health expenditure and increased health privatisation – e.g., expenditure on health in Zambia fell by 22% from 1982 to 1985, with a similar trend in other Sub Saharan African countries such as Zimbabwe, owing to the implementation of Structural Adjustment Programmes (Gilbert and Gilbert Reference Gilbert and Gilbert2004; Matshalaga Reference Matshalaga2000).

For South Africa, health services privatisation led to a persistent huge private-public funding imbalance. In 1994, approximately 23% of South Africans, many White, relied on private healthcare funded by insurance, which accounted for over 60% of the country’s healthcare expenditure (McIntyre et al. Reference McIntyre and Owen1994). Post-apartheid, South Africa retained a two-tier healthcare system: public sector healthcare catering for approximately 84% of the population, and private sector for the remaining 16% but accounting for over half of total healthcare expenditure in the country.

5. The birth of Discovery: a poster child for a ‘datafied’ neoliberal era

Discovery was founded in 1992 by Adrian Gore and Barry Swartzberg. Having worked in insurance as an actuary, Gore approached Rand Merchant Bank for start-up support of R 10 million (This was equivalent to approximately £2 million in 1992.) and permission to use their dormant insurance license. Discovery developed the Vitality programme in 1997. The proprietary behavioural change platform remains core to the Discovery business model, and the company has expanded into other behavioural economics-based products and services: life insurance, investments and more recently banking. Discovery operates in 41 global markets, notably the USA and China, although South Africa and the UK remain the primary markets. Discovery relies on data science both to lower its costs and ostensibly for positive social change (Discovery 2023a). This cyber-optimistic perspective is aligned with dominant narratives around digital technologies, which have become central to states’ policy responses to increase/improve service delivery in the pursuit of social transformation.

The ‘science of Vitality’ is based on four objectives: first, to use behavioural economics to identify risk factors; second, to encourage lifestyle changes to mitigate risks; third, to use a rewards-based system to incentivise healthy behaviour; and fourth, to produce an actuarial surplus (Vitality Discovery 2022). Underlying this is a shared value model that claims to redistribute risks of insurance more evenly through personal responsibility demonstrated through continuous engagement (Sadowski et al. Reference Sadowski, Lewis and Bednarz2024). The quest for individuals to continuously engage with their insurance providers through digital health marks a radical departure from traditional insurance companies, which sought to influence behaviour but didn’t have the infrastructural tools to create engagement and checks in real time about behaviour. While there are some variations of the product across markets, essentially, Vitality programme members earn points by continuously engaging with Discovery. This is achieved through providing evidence of healthier lifestyle choices that are logged in real time. These real-time logs require constant surveillance – e.g., exercising, eating healthy meals, smoking cessation activities. This surveillance works through a number of digital applications and system integrations that attach value to certain kinds of activities, such as purchasing healthy food in high-end grocery stores, that allow for integrated tracking, as evidence, for instance, of healthy food consumption. The constant engagement is rewarded for members by accumulating points (Global Vitality 2024). In return, Vitality points allow members to unlock rewards like discounts on groceries, flights, cinemas, accommodation, car hire, holiday packages, and rebates on life insurance premiums. Digital self-tracking activities (through digital wearable devices, smartphones and apps) are the most effective way of surveilling members. Vitality members can get up to 50% off smart fitness devices, including a ‘free’ Apple Watch by achieving weekly fitness goals (Discovery 2023b).

At the heart of Discovery’s social value model is an aggressive adoption of quantification and a techno-solutionist approach to health and healthcare, which enables it to accumulate increasing amounts of data. The digitalisation approach has also been effective in normalising some of the social harms of datafication, such as surveillance creep, with very little public scrutiny and resistance. Digitalisation has also led to successful partnerships with other companies, such as supermarkets, which see the Vitality infrastructure as a platform for advancing economic partnerships.

The Discovery case offers insights into the ways datafication infrastructures within health and wellness can lead to inequitable relations. It also illustrates how legal infrastructures are implicated in this. Discovery has operationalised legal mechanisms (contracts, mergers, acquisitions and property laws) to advance datafication of health and shape social relations through logics of economic rather than social value.

6. Contract law and individualised responsibility

Because Discovery uses behavioural economics to incentivise individuals to make healthier lifestyle choices, health and wellness are configured as individualised responsibility. Individuals who sign contracts for insurance opt into data generation through continuous tracking of behaviours, using secondary tracking devices (Jeanningros and McFall Reference Jeanningros and McFall2020). Established in 2016, in partnership with Apple, the ‘Vitality Active Rewards with Apple’ aims to leverage data-based insights through tracking users’ activities. Eligible Vitality members enter contracts by which they purchase an Apple Watch at a small upfront price with a tailored monthly repayment plan. Users sustaining/surpassing physical activity thresholds pay low/no repayments (Hafner et al. Reference Hafner, Pollard and van Stolk2020).

These reward partnerships between Discovery and other service providers (such as supermarkets, Apple, etc) are facilitated through commercial contracts that normalise a self-quantification surveillance culture. In this way, contract law also obscures power dynamics, positioning individuals as the principal beneficiaries in the commodification process without attention to the role of the infrastructural owners. More fundamentally, such application of contracts shifts attention from the social and structural determinants of health resulting from apartheid infrastructural legacies, and creates racialised health inequalities and vulnerabilities.

Vitality marketing programmes use images of relatively healthy White and Black urban young people engaging in elite activities such as swimming, playing tennis, cycling, rowing and driving expensive cars. This is used to construct an individualised aspirational lifestyle beyond the reach of the majority of Black South Africans, who struggle to pay basic bills and often have to rely on government grants for financial relief. It also models modernisation aspirations, where health and wellness are equated to and measured by a middle-class lifestyle, and by extension, access to capital and highly remunerated employment. Fundamentally, since the benefits of health data are disproportionately accrued by a small and predominantly wealthy segment, the Vitality model’s rhetoric of collective gain through participation is misleading.

Recent developments in AI have also opened up new frontiers for quantification. Discovery is expanding its complex insurance risk score behavioural activities in ways that visibly extend the data contractual relationship with users, with a recent shift to using AI to make Vitality a hyper-personalised disease management platform (Theunissen Reference Theunissen2024). For example, in partnership with RAND Europe, the Vitality programme has developed an algorithm that can predict a person’s longevity and years of good health, as well as recommend the actions they can take to improve quality of life (Vitality 2022). Discovery is partnering with an Australian-based data science firm, Quantium, which will use an AI algorithm to offer dynamic pricing models based on individual risk assessments and behaviours. Although secondary contracts are crucial for establishing new relationships between corporations for datafication in health contexts, users are seldom explicitly asked for informed consent when their data is repurposed for these processes. Furthermore, since hyper-personalisation does not account for broader systemic and structural determinants of health, it limits its scope to individualised risk predictions rather than addressing root causes of health inequalities (Sekalala and Chatikobo Reference Sekalala and Chatikobo2024).

7. The shared value model and the construction of expertise

Under the International Health Regulations, governments have an obligation to conduct and support health surveillance. During the COVID-19 pandemic, the South African government sought to leverage digital tools. This led to the development of the contact tracing application, COVID Alert SA. The government had to rely on expertise from Discovery, Apple and Google for its development (Department of Health 2020). Such expertise has also bolstered Discovery’s legitimacy and political capital to embed in health policy. For instance, Discovery went on to develop a COVID-19 personal resilience index for scheme members and the public to determine individual virus outcome risk scores. Such political capital from datafication activities and social value claims will likely give Discovery leverage in future negotiations with governments. Given that this data is non-representative of entire population groups, and does not factor in social determinants of health risks, such future partnerships for datafied infrastructures for health are likely to amplify racialised harms, as they are used to construct particular regimes of truths to solve problems that are neither automatable, nor based on individual life choices and behaviours – rather they are systemic. Disregarding the ways health system failures are connected to infrastructure configurations (such as social services), this idea of economic development has maintained and exacerbated differential access to opportunities and care.

Apart from the state and the individual, Discovery has also extended its datafication expertise to employers. Discovery has long marketed the Vitality product to employers as an effective tool for improving employee productivity through reduced health-related absenteeism. For instance, in a promotional guide to prospective corporate clients, Discovery claims that employees who engage with Vitality’s top-tier plans are 14% more productive and have lowered sick-day numbers by 46% (Discovery 2025; Vitality Health International 2022). By engaging in the datafication project through Vitality, social relations outside the traditional sphere of work and workplace are translated into institutions’ reproductive relational infrastructure. In this way, the individual and their relationships – private property, family and finances – are entangled in a permanent regulative enterprise for the economic benefit of corporations. While the causation between poor health and workplace productivity is supported by evidence (World Health Organization 2024), reducing health (let alone productivity) to a behavioural choice (as claimed through the social value rhetoric) rather than a systemic issue, underplays other structural determinants of poor health and wellness. In the case of South Africa, such structural determinants are tied to historical relations that sustained inequalities for marginalised groups. In the context of labour, these include inadequate economic protections due to a lack of progressive wage mobility, with cascading impacts on home conditions, work commute facilities, and health and wellness itself.

8. Mergers and acquisitions, and exclusionary transference

Through Discovery, we can also analyse the ways in which law is entangled with ownership and as a mechanism of labour extraction, and the increasing role of datafication in this process. Digital companies have often used acquisitions in order to expand datafication activities – the health insurance context is no different. The Council of Medical Schemes has actively encouraged mergers and acquisitions as a way to ensure economies of scale in the provision of medical aid. This has led to a shift towards larger schemes such as Quantum Medical Aid Society and WitsMed merging with the Discovery Health Medical Scheme. Such a merger also illustrates the shift in the basis for competition, with corporations such as Discovery that have significant datafication infrastructure standing to gain more from the increasing merger activity, even when there might be more suitable providers. For instance, Discovery Health Medical Scheme and WitsMed stated in their merger business proposal that Discovery’s extensive datafication infrastructure and effective risk-management strategies would aid competitive bargaining. However, such mergers tend to bring higher premiums for the joining members and enact generalised benefit structures that might not cater to the specific employee needs (Freitas Reference Freitas2017). In this way, localised solidarity mechanisms where employees could engage in collective bargaining for health insurance benefits with their employers are removed. Additionally, due to different medical aid options based on income threshold, those who are poorly paid on basic schemes are excluded from the merger and consolidation, thereby limiting benefits to certain groups often following racialised divides. For instance, only 10% of Black households have access to medical aid in South Africa compared to 70% of White households, as most Blacks remain in low-paying, irregular or informal sectors (Mhlanga and Garidzirai Reference Mhlanga and Garidzirai2020).

Those who wish to opt out through provisions of their contracts often have no alternatives. For example, the University of Witwatersrand Vice-Chancellor’s office and the Chairperson of the WitsMed board promoted the position that the amalgamation with Discovery was their employees’ ‘best and only viable option’ (Freitas Reference Freitas2017). Such rhetoric underscores how, individuals within institutitions are subject to (non)choice processes. While such decisions are often individualised, they have a collective implication on how racialised subjects are often boxed into making decisions which negatively affect their health and welfare, and have their solidarity mechanisms erased.

9. Property rights and digital enclosures

Proprietary designs govern the integration of Discovery’s Vitality, from digital health and wellness to insurance, investments and behavioural banking, and are protected within Intellectual Property (IP) law. Vitality’s expansion into spheres such as financial products illustrates the notion of ‘surveillance creep’ for maximum market exposure. There is often minimal public resistance and scrutiny to the gradual nature of such expansion. Current trajectories indicate that IP law will likely be deployed in future to prevent access to data not only by other corporations but also by the state. Data protection is framed through narratives of trust, and the threat to data is seen as something external:

This masks the underlying asymmetrical relations in the data value exchange: data protection from whom and for what? In its privacy statement, Discovery details the type and nature of personal information it collects about an individual – but in our view, the company neither provides an adequate explanation on how it uses data to ‘develop, monitor, and improve [its] systems and processes’, nor details the third parties with whom it shares this personal information.

Pro-market legal regimes have also sustained commercial interest over individual protections. With the increasing datafication, privacy protection laws have been insufficient in accounting for risks from advanced health and wellness analytics and AI, including relationships with cloud providers or analytics companies, which may handle data for purposes outside the initial scope (Botes Reference Botes2025). POPIA sets minimum requirements that must be met by companies when processing personal information of individuals; it applies to both private and public bodies and includes specific protections for biometric data. While the Act attempts to broadly define what constitutes personal information and processing, it has been criticised for not adequately covering privacy harms associated with surveillance capitalism and failing to consider sector-specific corporate actors (Cachalia and Klaaren Reference Cachalia and Klaaren2024). Through the National Health Act of 2003, the National Department of Health has responsibility for overseeing health data use, and has developed a national strategy for South Africa (2019–2024) that has focused obligations largely on national health systems, without clear oversight to private actors like health insurers, who are critical to the system (Sekalala, Rawson and Andanda Reference Sekalala, Rawson and Andanda2025). Moreover, regulations like POPIA require organisations processing personal information to ensure that collected data is complete, current and accurate – but with no provision stipulating how, leaving this responsibility with those organisations (Townsend and Botes Reference Townsend and Botes2023). This shift of responsibility invisibilises the processes of surveillance capitalism, providing very little accountability and scrutiny for the transference of public data into private domains.

Digital enclosures have both spatial and virtual dimensions, including the separation of people from one another and from their own lived experiences for surveillance (Andrejevic Reference Andrejevic2022). Commercial datafied infrastructures like Vitality rely on the logic of separating people and their lived experiences through the illusion of ‘ownership’. This is often reflected in digital apps through visualisations, user interface customisations, and download options, giving users a false sense that they own the data. Simultaneously, the systems’ data capture, processing, and resulting exploitation are hidden and heavily secured through property rights. This form of spatial enclosure is continuous, due to the replicability and dynamic nature of data, where multiple copies and versions can be developed and distributed within the digital ecosystem.

As illustrated above, we attempt to visibilise the ways in which property rights are deficient through the creation of privately held datasets, and by extension, associated claims, such as ‘social value model’ and ‘benefits’, which do not account for historical racialised determinants of poor health and inequitable access to infrastructures. We argue that the resulting health datasets that are being created are exacerbating data colonialities. Data extraction of this nature can lead to a distortion of knowledge forms, especially in places that have already experienced such displacements due to historical colonialism (Mumford Reference Mumford2022). This also compels us to think about the ways regulatory transformation could inform accountability measures on how health data held in private infrastructures is used to make decisions about society’s health and well-being.

10. (Digital) Health Reforms and Legal Contradictions

Post-colonial spaces are profoundly interlinked and shaped by past developments. In South Africa, transformative constitutionalism has been adopted as part of the progressive legal reforms post-1994, based on active and historical self-conscious duty for equitable social rights, affirmative action, participatory governance, multiculturalism and redress (Geduld Reference Geduld2020). The South African Constitution made some changes to property rights, considering the historical harms and the ongoing colonialities for particular social groups. While marking a shift from the apartheid legal order, premised on giving the state considerable power over social processes, the new legal structure provided private health actors considerable access, protection and power to shape and structure social benefits, often wielding more significant political clout. Contemporary legal infrastructures occupy a Janus-faced existence of attempting to serve two masters, which can further perpetuate oppression and discrimination (Bachmann and Frost Reference Bachmann and Frost2012). This calls for rethinking digital health regulatory systems to consider the interplay between different legal forms and the social context. For the government, the task is to ‘construct a substantive conception of the rule of law, which values the rectification of [social harms] above legal certainty’, as that will always play into the hands of infrastructural winners (ibid. 2012, p. 327). For scholars, debates around digital health inequalities, surveillance capitalism and coloniality need to be complemented by an analysis of the role of law in reinforcing systems, structures, institutions, and procedures of historically-embedded racialised harm.

Our attempt is not to downplay instances where legal infrastructures in post-colonial states have also provided means for challenging the political economy of health access and addressing structural and racialised inequalities. There have indeed been attempts at using legal mechanisms for redress in South Africa, such as the Medical Schemes Act 131 of 1998, which mandated open enrolment (except for restricted schemes), community-rating provisions, and prescribed minimum benefits to prevent direct and indirect discrimination against racial groups. Despite this, the persistent racialised distribution of capital has meant that it is mostly Whites and a few Black elites who can afford coverage and high out-of-pocket costs to access well-equipped private health systems (Golomski Reference Golomski2018).

Efforts to align health reforms with universalist principles have been ongoing for nearly 100 years in South Africa. These attempts have culminated in the overhaul of health insurance through a social solidarity and equity intervention of risk cross-subsidies, income cross-subsidies, and a single-purchaser model in healthcare financing, known as the National Health Insurance (NHI) (Whyle and Olivier Reference Whyle and Olivier2023). While the NHI has been largely welcomed, medical aid schemes such as Discovery Health have firmly opposed its implementation approaches. Discovery has consistently maintained the strong view that limiting the role of medical schemes would be counterproductive to the NHI, as the government has insufficient resources to meet the needs of all South Africans. Discovery argues this will likely lead to a violation of the constitutional rights of citizens, critical-skills drain, negative local and international investors’ confidence, and an increased tax burden (Discovery 2024). Stronger views can also be noted from the leading opposition party in South Africa, the Democratic Alliance (DA), who have characterised the NHI as a reckless and a ‘cheap political ploy that will do nothing to address the dire state of public healthcare in all provinces except the Western Cape [a DA-governed province], while creating a centralised R200 billion fund vulnerable to corruption under the direct control of the Minister of Health’ (Democratic Alliance Reference Alliance2024). The South African Treasury stated that the government is likely to maintain the current role of medical schemes in the provision of health services, as it cannot finance the system independently (Bhana Reference Bhana2025).

The NHI reform is already facing legal obstacles. The Gauteng High Court has recently ruled that President Ramaphosa’s decision to sign the NHI bill into law should be subject to judicial review, and ordered him to submit comprehensive records of what informed his decision-making.Footnote ² This comes after a legal challenge by the South African Private Practitioners Forum and the Board of Health Funders, who submitted that the legislative process had procedural flaws, including insufficient public consultation. Similarly, the South African Medical Association announced that it will challenge the Act’s constitutionality in the High Court, on the grounds that it will likely prejudice doctors and patients due to a lack of clarity on the type of services to be covered, medical services procurement, and how private sector doctors will be covered against medico-legal claims (Metelerkamp Reference Metelerkamp2025). The signing of the NHI in May 2024, before the consequential national elections in which the ANC lost its majority for the first time in 30 years, triggered public scepticism on the sincerity of the government in inaugurating long overdue healthcare reforms as a duty of care, rather than merely as a mechanism of political survival. The ambiguities on key administrative components and implementation modalities of the NHI illustrate how infrastructural entanglements – such as the administration and bureaucratisation of governmental services and the distribution of political power – are often instrumental in maintaining the status quo. Moreover, it sheds light on how political elites are complicit in shaping legal infrastructures in ways that may be counterproductive to social solidary.

The recurring question on the role of the private sector in the NHI compels us to ask whether corporations fundamentally have a role in institutional infrastructure reforms. The state’s initial motivations for integrating the two healthcare models were premised on the idea that the public could benefit from private health infrastructures without prejudicing them, since the government would effectively pay for such access. After all, the state already underwrites a private healthcare sector through a constellation of direct and indirect subsidies. Firstly, the state invests significant resources in the training of healthcare professionals. Secondly, as a major employer, the state allocates billions of rands annually to medical aid contributions for public sector employees. Thirdly, taxpayers can claim tax rebates on medical aid expenses, which amount to approximately R37 billion in 2024 (Ramaphosa Reference Ramaphosa2024).

It is our view that a more equitable health infrastructure hinges on robust legal reforms that prioritise a solidarity and care model oriented towards population health outcomes, and accounting for how socio-economic relations and disparities directly affect health and wellness. Such legal infrastructure reforms should be more explicit about the obligations of insurance companies in including the entire population in healthcare as part of licensing agreements, encouraging a more commons-based approach to healthcare provision, as well as ensuring that datasets that inform healthcare interventions are more representative. From an infrastructural perspective, this would ensure that encounters between datafication and legal infrastructures contribute towards a social value proposition that centres citizens – rather than corporations and elites – as the real beneficiaries of digital health transformation.