Data Infrastructures and Inequities: Why Does Reproductive Health Surveillance in India Need Our Urgent Attention?
In order to bring out certain conceptual and procedural problems with health monitoring in the Indian context, this article by Aayush Rathi and Ambika Tandon posits health monitoring as surveillance and not merely as a “data problem.” Casting a critical feminist lens, the historicity of surveillance practices unveils the gendered power differentials wedded into taken-for-granted “benign” monitoring processes. The unpacking of the Mother and Child Tracking System and the National Health Stack reveals the neo-liberal aspirations of the Indian state.
The article was first published by EPW Engage, Vol. 54, Issue No. 6, on 9 February 2019.
Framing Reproductive Health as a Surveillance Question
The approach of the postcolonial Indian state to healthcare has been Malthusian, with the prioritisation of family planning and birth control (Hodges 2004). Supported by the notion of socio-economic development arising out of a “modernisation” paradigm, the target-based approach to achieving reduced fertility rates has shaped India’s reproductive and child health (RCH) programme (Simon-Kumar 2006).
This is also the context in which India’s abortion law, the Medical Termination of Pregnancy (MTP) Act, was framed in 1971, placing the decisional privacy of women seeking abortions in the hands of registered medical practitioners. The framing of the MTP act invisibilises females seeking abortions for non-medical reasons within the legal framework. The exclusionary provisions only exacerbated existing gaps in health provisioning, as access to safe and legal abortions had already been curtailed by severe geographic inequalities in funding, infrastructure, and human resources. The state has concomitantly been unable to meet contraceptive needs of married couples or reduce maternal and infant mortality rates in large parts of the country, mediating access along the lines of class, social status, education, and age (Sanneving et al 2013).
While the official narrative around the RCH programme transitioned to focus on universal access to healthcare in the 1990s, the target-based approach continues to shape the reality on the ground. The provision of reproductive healthcare has been deeply unequal and, in some cases, in hospitals. These targets have been known to be met through the practice of forced, and often unsafe, sterilisation, in conditions of absence of adequate provisions or trained professionals, pre-sterilisation counselling, or alternative forms of contraception (Sama and PLD 2018). Further, patients have regularly been provided cash incentives, foreclosing the notion of free consent, especially given that the target population of these camps has been women from marginalised economic classes in rural India.
Placing surveillance studies within a feminist praxis allows us to frame the reproductive health landscape as more than just an ill-conceived, benign monitoring structure. The critical lens becomes useful for highlighting that taken-for-granted structures of monitoring are wedded with power differentials: genetic screening in fertility clinics, identification documents such as birth certificates, and full-body screeners are just some of the manifestations of this (Adrejevic 2015). Emerging conversations around feminist surveillance studies highlight that these data systems are neither benign nor free of gendered implications (Andrejevic 2015). In continual remaking of the social, corporeal body as a data actor in society, such practices render some bodies normative and obfuscate others, based on categorisations put in place by the surveiller.
In fact, the history of surveillance can be traced back to the colonial state where it took the form of systematic sexual and gendered violence enacted upon indigenous populations in order to render them compliant (Rifkin 2011; Morgensen 2011). Surveillance, then, manifests as a “scientific” rationalisation of complex social hieroglyphs (such as reproductive health) into formats enabling administrative interventions by the modern state. Lyon (2001) has also emphasised how the body emerged as the site of surveillance in order for the disciplining of the “irrational, sensual body”—essential to the functioning of the modern nation-state—to effectively happen.
Questioning the Information and Communications Technology for Development (ICT4D) and Big Data for Development (BD4D) Rhetoric
Information and Communications Technology (ICT) and data-driven approaches to the development of a robust health information system, and by extension, welfare, have been offered as solutions to these inequities and exclusions in access to maternal and reproductive healthcare in the country.
The move towards data-driven development in the country commenced with the introduction of the Health Management Information System in Andhra Pradesh in 2008, and the Mother and Child Tracking System (MCTS) nationally in 2011. These are reproductive health information systems (HIS) that collect granular data about each pregnancy from the antenatal to the post-natal period, at the level of each sub-centre as well as primary and community health centre. The introduction of HIS comprised cross-sectoral digitisation measures that were a part of the larger national push towards e-governance; along with health, thirty other distinct areas of governance, from land records to banking to employment, were identified for this move towards the digitalised provisioning of services (MeitY 2015).
The HIS have been seen as playing a critical role in the ecosystem of health service provision globally. HIS-based interventions in reproductive health programming have been envisioned as a means of: (i) improving access to services in the context of a healthcare system ridden with inequalities; (ii) improving the quality of services provided, and (iii) producing better quality data to facilitate the objectives of India’s RCH programme, including family planning and population control. Accordingly, starting 2018, the MCTS is being replaced by the RCH portal in a phased manner. The RCH portal, in areas where the ANMOL (ANM Online) application has been introduced, captures data real-time through tablets provided to health workers (MoHFW 2015).
A proposal to mandatorily link the Aadhaar with data on pregnancies and abortions through the MCTS/RCH has been made by the union minister for Women and Child Development as a deterrent to gender-biased sex selection (Tembhekar 2016). The proposal stems from the prohibition of gender-biased sex selection provided under the Pre-Conception and Pre-Natal Diagnostics Techniques (PCPNDT) Act, 1994. The approach taken so far under the PCPNDT Act, 2014 has been to regulate the use of technologies involved in sex determination. However, the steady decline in the national sex ratio since the passage of the PCPNDT Act provides a clear indication that the regulation of such technology has been largely ineffective. A national policy linking Aadhaar with abortions would be aimed at discouraging gender-biased sex selection through state surveillance, in direct violation of a female’s right to decisional privacy with regards to their own body.
Linking Aadhaar would also be used as a mechanism to enable direct benefit transfer (DBT) to the beneficiaries of the national maternal benefits scheme. Linking reproductive health services to the Aadhaar ecosystem has been critiqued because it is exclusionary towards women with legitimate claims towards abortions and other reproductive services and benefits, and it heightens the risk of data breaches in a cultural fabric that already stigmatises abortions. The bodies on which this stigma is disproportionately placed, unmarried or disabled females, for instance, experience the harms of visibility through centralised surveillance mechanisms more acutely than others by being penalised for their deviance from cultural expectations. This is in accordance with the theory of "data extremes,” wherein marginalised communities are seen as living on the extremes of data capture, leading to a data regime that either refuses to recognise them as legitimate entities or subjects them to overpolicing in order to discipline deviance (Arora 2016). In both developed and developing contexts, the broader purpose of identity management has largely been to demarcate legitimate and illegitimate actors within a population, either within the framework of security or welfare.
Potential Harms of the Data Model of Reproductive Health Provisioning
Informational privacy and decisional privacy are critically shaped by data flows and security within the MCTS/RCH. No standards for data sharing and storage, or anonymisation and encryption of data have been implemented despite role-based authentication (NHSRC and Taurus Glocal 2011). The risks of this architectural design are further amplified in the context of the RCH/ANMOL where data is captured real-time. In the absence of adequate safeguards against data leaks, real-time data capture risks the publicising of reproductive health choices in an already stigmatised environment. This opens up avenues for further dilution of autonomy in making future reproductive health choices.
Several core principles of informational privacy, such as limitations regarding data collection and usage, or informed consent, also need to be reworked within this context.[1] For instance, the centrality of the requirement of “free, informed consent” by an individual would need to be replaced by other models, especially in the context of reproductive health of rape survivors who are vulnerable and therefore unable to exercise full agency. The ability to make a free and informed choice, already dismantled in the context of contemporary data regimes, gets further precluded in such contexts. The constraints on privacy in decisions regarding the body are then replicated in the domain of reproductive data collection.
What is uniform across these digitisation initiatives is their treatment of maternal and reproductive health as solely a medical event, framed as a data scarcity problem. In doing so, they tend to amplify the understanding of reproductive health through measurable indicators that ignore social determinants of health. For instance, several studies conducted in the rural Indian context have shown that the degree of women’s autonomy influences the degree of usage of pregnancy care, and that the uptake of pregnancy care was associated with village-level indicators such as economic development, provisioning of basic infrastructure and social cohesion. These contextual factors get overridden in pervasive surveillance systems that treat reproductive healthcare as comprising only of measurable indicators and behaviours, that are dependent on individual behaviour of practitioners and women themselves, rather than structural gaps within the system.
While traditionally associated with state governance, the contemporary surveillance regime is experienced as distinct from its earlier forms due to its reliance on a nexus between surveillance by the state and private institutions and actors, with both legal frameworks and material apparatuses for data collection and sharing (Shepherd 2017). As with historical forms of surveillance, the harms of contemporary data regimes accrue disproportionately among already marginalised and dissenting communities and individuals. Data-driven surveillance has been critiqued for its excesses in multiple contexts globally, including in the domains of predictive policing, health management, and targeted advertising (Mason 2015). In the attempts to achieve these objectives, surveillance systems have been criticised for their reliance on replicating past patterns, reifying proximity to a hetero-patriarchal norm (Haggerty and Ericson 2000). Under data-driven surveillance systems, this proximity informs the preexisting boxes of identity for which algorithmic representations of the individual are formed. The boxes are defined contingent on the distinct objectives of the particular surveillance project, collating disparate pieces of data flows and resulting in the recasting of the singular offline self into various 'data doubles' (Haggerty and Ericson 2000). Refractive, rather than reflective, the data doubles have implications for the physical, embodied life of individual with an increasing number of service provisioning relying on the data doubles (Lyon 2001). Consider, for instance, apps on menstruation, fertility, and health, and wearables such as fitness trackers and pacers, that support corporate agendas around what a woman’s healthy body should look, be or behave like (Lupton 2014). Once viewed through the lens of power relations, the fetishised, apolitical notion of the data “revolution” gives way to what we may better understand as “dataveillance.”
Towards a Networked State and a Neo-liberal Citizen
Following in this tradition of ICT being treated as the solution to problems plaguing India’s public health information system, a larger, all-pervasive healthcare ecosystem is now being proposed by the Indian state (NITI Aayog 2018). Termed the National Health Stack, it seeks to create a centralised electronic repository of health records of Indian citizens with the aim of capturing every instance of healthcare service usage. Among other functions, it also envisions a platform for the provisioning of health and wellness-based services that may be dispensed by public or private actors in an attempt to achieve universal health coverage. By allowing private parties to utilise the data collected through pullable open application program interfaces (APIs), it also fits within the larger framework of the National Health Policy 2017 that envisions the private sector playing a significant role in the provision of healthcare in India. It also then fits within the state–private sector nexus that characterises dataveillance. This, in turn, follows broader trends towards market-driven solutions and private financing of health sector reform measures that have already had profound consequences on the political economy of healthcare worldwide (Joe et al 2018).
These initiatives are, in many ways, emblematic of the growing adoption of network governance reform by the Indian state (Newman 2001). This is a stark shift from its traditional posturing as the hegemonic sovereign nation state. This shift entails the delayering from large, hierarchical and unitary government systems to horizontally arranged, more flexible, relatively dispersed systems.[2] The former govern through the power of rules and law, while the latter take the shape of self-regulating networks such as public–private contractual arrangements (Snellen 2005). ICTs have been posited as an effective tool in enabling the transition to network governance by enhancing local governance and interactive policymaking enabling the co-production of knowledge (Ferlie et al 2011). The development of these capabilities is also critical to addressing “wicked problems” such as healthcare (Rittel and Webber 1973).[3] The application of the techno-deterministic, data-driven model to reproductive healthcare provision, then, resembles a fetishised approach to technological change. The NHSRC describes this as the collection of data without an objective, leading to a disproportional burden on data collection over use (NHSRC and Taurus Glocal 2011).
The blurring of the functions of state and private actors is reflective of the neo-liberal ethic, which produces new practices of governmentality. Within the neo-liberal framework of reproductive healthcare, the citizen is constructed as an individual actor, with agency over and responsibility for their own health and well-being (Maturo et al 2016).
“Quantified Self” of the Neo-liberal Citizen
Nowhere can the manifestation of this neo-liberal citizen can be seen as clearly as in the “quantified self” movement. The quantified self movement refers to the emergence of a whole range of apps that enable the user to track bodily functions and record data to achieve wellness and health goals, including menstruation, fertility, pregnancies, and health indicators in the mother and baby. Lupton (2015) labels this as the emergence of the “digitised reproductive citizen,” who is expected to be attentive to her fertility and sexual behaviour to achieve better reproductive health goals. The practice of collecting data around reproductive health is not new to the individual or the state, as has been demonstrated by the discussion above. What is new in this regime of datafication under the self-tracking movement is the monetisation of reproductive health data by private actors, the labour for which is performed by the user. Focusing on embodiment draws attention to different kinds of exploitation engendered by reproductive health apps. Not only is data about the body collected and sold, the unpaid labour for collection is extracted from the user. The reproductive body can then be understood as a cyborg, or a woman-machine hybrid, systematically digitising its bodily functions for profit-making within the capitalist (re)production machine (Fotoloulou 2016). Accordingly, all major reproductive health tracking apps have a business model that relies on selling information about users for direct marketing of products around reproductive health and well-being (Felizi and Varon nd).
As has been pointed out in the case of big data more broadly, reproductive health applications (apps) facilitate the visibility of the female reproductive body in the public domain. Supplying anonymised data sets to medical researchers and universities fills some of the historical gaps in research around the female body and reproductive health. Reproductive and sexual health tracking apps globally provide their users a platform to engage with biomedical information around sexual and reproductive health. Through group chats on the platform, they are also able to engage with experiential knowledge of sexual and reproductive health. This could also help form transnational networks of solidarity around the body and health (Fotopoulou 2016).
This radical potential of network-building around reproductive and sexual health is, however, tempered to a large extent by the reconfiguration of gendered stereotypes through these apps. In a study on reproductive health apps on Google Play Store, Lupton (2014) finds that products targeted towards female users are marketed through the discourse of risk and vulnerability, while those targeted towards male users are framed within that of virility. Apart from reiterating gendered stereotypes around the male and female body, such a discourse assumes that the entire labour of family planning is performed by females. This same is the case with the MCTS/RCH.
Technological interventions such as reproductive health apps as well as HIS are based on the assumption that females have perfect control over decisions regarding their own bodies and reproductive health, despite this being disproved in India. The Guttmacher Institute (2014) has found that 60% of women in India report not having control over decisions regarding their own healthcare. The failure to account for the husband or the family as stakeholder in decision-making around reproductive health has been a historical failure of the family planning programme in India, and is now being replicated in other modalities. This notion of an autonomous citizen who is able to take responsibility of their own reproductive health and well-being does not hold true in the Indian context. It can even be seen as marginalising females who have already been excluded from the reproductive health system, as they are held responsible for their own inability to access healthcare.
Concluding Remarks
The interplay that emerges between reproductive health surveillance and data infrastructures is a complex one. It requires the careful positioning of the political nature of data collection and processing as well as its hetero-patriarchal and colonial legacies, within the need for effective utilisation of data for achieving developmental goals. Assessing this discourse through a feminist lens identifies the web of power relations in data regimes. This problematises narratives of technological solutions for welfare provision.
The reproductive healthcare framework in India then offers up a useful case study to assess these concerns. The growing adoption of ICT-based surveillance tools to equalise access to healthcare needs to be understood in the socio-economic, legal, and cultural context where these tools are being implemented. Increased surveillance has historically been associated with causing the structural gendered violence that it is now being offered as a solution to. This is a function of normative standards being constructed for reproductive behaviour that necessarily leave out broader definitions of reproductive health and welfare when viewed through a feminist lens. Within the larger context of health policymaking in India, moves towards privatisation then demonstrate the peculiarity of dataveillance as it functions through an unaccountable and pervasive overlapping of state and private surveillance practises. It remains to be seen how these trends in ICT-driven health policies affect access to reproductive rights and decisional privacy for millions of females in India and other parts of the global South.