A central issue shaping the 2020 electoral debates is the role of public and private interests in the US health care system, and this issue has only grown more important since the emergence of COVID-19. Even during a pandemic that has caused many people to lose their jobs and by extension, their health insurance, Donald Trump and other prominent Republicans continue to call for an end to the Affordable Care Act (ACA) (Luthi 2020). Democrats, on the other hand, are split between a reformist vision that would preserve the ACA and a more progressive vision that would replace it with a single-payer health care system.<\/p>\n\n\n\n
Like politicians, anthropologists also debate the role of public and private interests in health care systems throughout the world. While anthropological and mainstream political discussions have focused largely on the role of the pharmaceutical, biotechnology, and insurance industries (e.g., Dumit 2012; Kaufman 2015; Rajan 2017), here I examine a different site of capitalist activity: the growing market in smart health technologies. As COVID-19 continues to spread, health professionals are increasingly turning to these technologies to avoid the risks of in-person contact and to carry out containment efforts (Nielo 2020; Seabrook 2020). This is also leading digital health advocates to amplify their calls for the post-pandemic integration of smart technologies into routine health care practices. As I describe below, this situation raises questions about laws and policies regulating data privacy and commodification.<\/p>\n\n\n\n
Although COVID-19 is accelerating the adoption of digital health care practices, many such practices have existed since before the pandemic. They are known by multiple names\u2014digital health, eHealth, mHealth, Health 2.0, etc.\u2014but they all entail the use of networked technologies to facilitate clinical health care functions (Ruckenstein and Sch\u00fcll 2017). Central to these developments is the \u201cInternet of Things\u201d (IoT), or the ever-expanding stock of smart technologies that have become pervasive elements of everyday life. The IoT is comprised of a broad range of mass-manufactured technologies, with health-related devices and applications being an area of significant economic and ideological investment (Grand View Research 2020; Larner 2018; Mind Commerce 2020; Sch\u00fcll 2016).<\/p>\n\n\n\n
Digital health advocates argue that the increasing use of such technologies during the pandemic offers an opportunity for their long-term adoption. They suggest that continuing to increase the use of these devices could make health care more convenient, efficient, and effective by reducing the need for office visits and providing physicians with round-the-clock patient data that will enable them to spot and address health issues as early as possible (Oelrich and Langlands 2020). This logic has given rise to visions of a \u201cnew connected health consumer,\u201d a subject perpetually attached to \u201cremote monitoring technologies,\u201d or smart devices that alert physicians when they produce readings that fall outside of standardized ranges (Shapiro 2020). This involves the enrollment of commercial products like the FitBit, Apple Watch, and iPhone into clinical care on the basis of advertised claims about their ability to continuously and reliably monitor health indicators, such as heartbeat, physical activity, and calories burned. These private corporations own and control sensitive health data that will theoretically help users and physicians maintain and improve health.<\/p>\n\n\n\n
In contrast to the most enthusiastic advocates, medical anthropologists have raised a number of critical questions and observations regarding smart health technologies (Greenfield 2016, 2015; Lupton 2016; Neff and Nafus 2016; Ruckenstein and Pantzar 2017; Taminen and Holmgren 2016). One important observation to come out of this work is that there is a great deal of uncertainty as to how effectively the use of these technologies can be scaled up and institutionalized. As Ruckenstein and Sch\u00fcll note, the underlying vision driving digital health advocacy \u201cis mostly speculative, promissory, and, as yet, unrealized\u201d (2017: 262).<\/p>\n\n\n\n
Beyond pointing out the uncertainty regarding the ability of digital health care to deliver on its promises, anthropologists have also raised questions about the relationship between digital health technologies and neoliberal modes of governance and subjectification. Challenging Lupton\u2019s (2013) claim that these technologies can be seen primarily as instruments of neoliberal responsibilization, Natasha Dow Sch\u00fcll (2016) argues that \u201cdatafication\u201d is a more useful analytic. From her perspective, digital health practices fall \u201csomewhere between enterprise and submission.\u201d The datafied subject of digital health is a \u201cchoosing subject, but one who is constitutionally ill-equipped to make rational, healthy choices.\u201d To inhabit a datafied subject position is to \u201cheavily value one\u2019s choices and the need to be responsible for them while, at the same time, relieving oneself of responsibility by delegating it to external technology\u201d (Sch\u00fcll 2016: 12).<\/p>\n\n\n\n
Sch\u00fcll suggests that one reason datafied subjects engage in these acts of delegation is to relieve the burdens of living under what Adams et al. describe as a neoliberal \u201cregime of anticipation\u201d\u2014a regime in which \u201cthe obligation to \u2018stay informed\u2019 about possible futures has become mandatory for good citizenship and morality, engendering alertness and vigilance as normative affective states\u201d (2009: 259). From Sch\u00fcll\u2019s perspective, the use of digital health devices can be seen as a method of partially outsourcing the embodied stresses of neoliberal anticipation and the health-focused forms of responsibility associated with it. <\/p>\n\n\n\n
Sch\u00fcll\u2019s notion of datafication raises important insights about how digital health technologies are contributing to the production of new modes of neoliberal subjectification, and medical anthropologists can continue to play an important role in documenting and analyzing this process as it unfolds among groups inhabiting diverse structural conditions. As Ruckenstein and Sch\u00fcll (2017: 271) note, most existing anthropological studies of digital health technologies focus on relatively wealthy, highly educated, and cosmopolitan consumers, and I would add that they also tend to focus on consumers who are developmentally marked as adults. As the COVID-19 pandemic opens up new pathways for the nation-wide implementation of digital health care, medical anthropologists can productively attend to the entanglement of social inequalities and public and private interests that are shaping processes of datafication.<\/p>\n\n\n\n
It is particularly important to critically evaluate these issues during election season, as digital health is one of the Trump administration\u2019s priorities for health care reform. The administration\u2019s 2018 budget offered funding for the creation of the Digital Health Center of Excellence (DHCE), which will be overseen by the Food and Drug Administration (FDA) (Lim 2019). Scott Gottlieb, the physician, venture capitalist, and former commissioner of the FDA who proposed the creation of the DHCE has stated that one of the center\u2019s primary goals will be to \u201chelp establish more efficient regulatory paradigms, consider building new capacity to evaluate and recognize third-party certifiers, and support a cybersecurity unit to complement the advances in software-based devices\u201d (Mulero 2019).<\/p>\n\n\n\n
The DHCE is just one example of how public and private interests are becoming entangled in ideologies and practices of digital health. As the election unfolds, it could be useful for medical anthropologists to critically evaluate how presidential candidates and their respective parties are framing issues of digital health in their campaign rhetoric and policy proposals. It could also be useful to consider how tech companies, big data firms, health care organizations, and other private interests are shaping and being shaped by emerging laws and public policies. As more and more populations become targets of datafication in the name of improving national health, new inequalities and relationships to digital technologies will almost certainly emerge.<\/p>\n\n\n\n
As a scholar whose work is situated at the intersection of medical anthropology and childhood studies, I find it particularly important to consider how increasing datafication will affect pediatric health care practices. Many young people born today will become the most digitally monitored individuals to have ever existed. Given their legal status as minors, one might assume that control over that data would belong to their parents or legal guardians. Yet data privacy laws in the United States are notoriously lax, and the primary law which applies to children\u2019s data, the Children\u2019s Online Privacy Protection Act (COPPA), has been described as \u201ca sort of \u2018opt-in\u2019 privacy band-aid\u201d (Johnson 2018). In other words, there are many ways for tech companies to work around this law in order to acquire and sell children\u2019s data without parental consent. Furthermore, while it might be assumed that data privacy laws are stricter when it comes to devices that monitor health data, this is not necessarily the case. While the US government does have more stringent laws regulating products classified as \u201cmedical technologies,\u201d many devices associated with digital health practices\u2014for example, smart phones and watches\u2014are classified as non-<\/em>medical (U.S. Food and Drug Administration, 2020). The aforementioned fact that the FDA\u2019s current plans for the future of digital health involve privatizing device certification processes and making regulatory paradigms \u201cmore efficient\u201d does not bode well for those who value data privacy, or for consumers who are unaware of the extent to which their data is surveilled and commodified. One need only point to the Cambridge Analytica scandal surrounding the U.S. presidential election of 2016 to demonstrate the potential dangers of loosely regulated datafication (Chang 2018; Laterza 2018).<\/p>\n\n\n\n As the project of digital health care continues to develop and expand during this election year and beyond, medical anthropologists can play a useful role in advocating for laws and policies that rigorously protect the rights of all people over the health data generated by a broad range of devices, not just those formally classified as medical. In the absence of such laws, the digitally mediated practices which the relatively privileged members of self-tracking groups describe as a voluntary attempt to delegate the labor of anticipation could, for a much larger number of less privileged adults and children, become a doctor-prescribed form of data exploitation that only further entrenches social inequalities. <\/p>\n\n\n\n Anthony Wright<\/strong> received his Ph.D. in medical anthropology from the University of California, Berkeley and San Francisco in 2019, and he is currently an assistant professor of childhood studies at Rutgers University, Camden. His research focuses on how various forms of illness, violence, and inequality shape the digital mediation of childhood and youth, particularly in the United States and Mexico.<\/p>\n\n\n\n Works Cited<\/strong><\/p>\n\n\n\n Adams, Vincanne, Michelle Murphy, and Adele E Clarke. 2009. \u201cAnticipation: Technoscience, Life, Affect, Temporality.\u201d Subjectivity<\/em> 28 (1): 246\u201365. https:\/\/doi.org\/10.1057\/sub.2009.18<\/a>.<\/p>\n\n\n\n Chang, Alvin. 2018. \u201cThe Facebook and Cambridge Analytica Scandal, Explained with a Simple Diagram.\u201d Vox. May 2, 2018. https:\/\/www.vox.com\/policy-and-politics\/2018\/3\/23\/17151916\/facebook-cambridge-analytica-trump-diagram<\/a>.<\/p>\n\n\n\n Dumit, Joseph. 2012. Drugs for Life: How Pharmaceutical Companies Define Our Health<\/em>. Durham, NC: Duke University Press.<\/p>\n\n\n\n Grand View Research. 2020. \u201cWearable Medical Device Market Size, Share & Trends Analysis Report By Product Type (Diagnostic, Therapeutic, Respiratory), By Site (Strap\/Clip\/Bracelet, Handheld), By Application, And Segment Forecasts, 2020 \u2013 2027.\u201d Market analysis 978-1-68038-724\u20137. https:\/\/www.grandviewresearch.com\/industry-analysis\/wearable-medical-devices-market.<\/a><\/p>\n\n\n\n Greenfield, Dana. 2016. \u201cDeep Data: Notes on the n of 1<\/em>.\u201d In Quantified: Biosensing Technologies in Everyday Life<\/em>, edited by Dawn Nafus. Cambridge, Massachusetts: The MIT Press.<\/p>\n\n\n\n Greenfield, Dana Emily. 2015. \u201cHomo Experimentus: Digital Selves and Digital Health in the Age of Innovation.\u201d Doctoral dissertation, San Francisco, CA: University of California. https:\/\/escholarship.org\/uc\/item\/8h92q6rt<\/a>.<\/p>\n\n\n\n Johnson, Steven. 2018. \u201cThe Bargain at the Heart of the Kid Internet.\u201d The Atlantic<\/em>. April 12, 2018. https:\/\/www.theatlantic.com\/family\/archive\/2018\/04\/child-data-privacy\/557840\/<\/a>.<\/p>\n\n\n\n Kaufman, Sharon R. 2015. Ordinary Medicine: Extraordinary Treatments, Longer Lives, and Where to Draw the Line<\/em>. Critical Global Health. Durham\u202f; London: Duke University Press.<\/p>\n\n\n\n Larner, Michael. 2018. \u201cDigital Health: Disruptor Analysis, Country Readiness & Technology Forecasts 2018-2023.\u201d Juniper Research. https:\/\/www.juniperresearch.com\/researchstore\/key-vertical-markets\/digital-health-market-research-report?utm_campaign=digitalhealth19pr2&utm_source=businesswire&utm_medium=email.<\/a><\/p>\n\n\n\n Laterza, Vito. 2018. \u201cCambridge Analytica, Independent Research and the National Interest.\u201d Anthropology Today<\/em> 34 (3): 1\u20132. https:\/\/doi.org\/10.1111\/1467-8322.12430<\/a>.<\/p>\n\n\n\n Lupton, Deborah. 2016. The quantified self<\/em>. Cambridge: Polity Press.<\/p>\n\n\n\n Lupton, Deborah. 2013. \u201cThe Digitally Engaged Patient: Self-Monitoring and Self-Care in the Digital Health Era.\u201d Social Theory & Health<\/em> 11 (3): 256\u201370. https:\/\/doi.org\/10.1057\/sth.2013.10<\/a>.<\/p>\n\n\n\n Luthi, Susannah. 2020. \u201cTrump Will Urge Supreme Court to Strike down Obamacare.\u201d Politico. May 6, 2020. https:\/\/www.politico.com\/news\/2020\/05\/06\/trump-supreme-court-obamacare-240366<\/a>.<\/p>\n\n\n\n Mind Commerce. 2020. \u201cWorldwide Wearable Technology Market (2020 to 2025).\u201d Cision PR Newswire. February 27, 2020. https:\/\/www.prnewswire.com\/news-releases\/worldwide-wearable-technology-market-2020-to-2025\u2014learn-about-new-wearable-technology-business-models-such-as-pay-per-gaze-301012859.html<\/a>.<\/p>\n\n\n\n Mulero, Ana. 2019. \u201cDigital Health: \u2018Connecting the Dots\u2019 Across FDA Centers.\u201d Regulatory Affairs Professionals Society. April 24, 2019. https:\/\/www.raps.org\/news-and-articles\/news-articles\/2019\/4\/digital-health-connecting-the-dots-across-fda-c<\/a>.<\/p>\n\n\n\n Neff, Gina, and Dawn Nafus. 2016. Self-Tracking<\/em>. The MIT Press Essential Knowledge Series. Cambridge, Massachusetts: The MIT Press.<\/p>\n\n\n\n Nielo, David. 2020. \u201cHow Covid-19 Contact Tracing Works on Your Phone.\u201d Wired. June 7, 2020. https:\/\/www.wired.com\/story\/covid-19-contact-tracing-apple-google\/<\/a>.<\/p>\n\n\n\n Oelrich, Teri, and Bryan Langlands. 2020. \u201cThe Coronavirus Pandemic Has Boosted Telehealth; Here\u2019s How Existing Spaces Can Support Virtual Visits.\u201d Forbes. June 8, 2020. https:\/\/www.forbes.com\/sites\/coronavirusfrontlines\/2020\/06\/08\/the-coronavirus-pandemic-has-boosted-telehealth-heres-how-existing-spaces-can-support-virtual-visits\/#5f4f8a877560<\/a>.<\/p>\n\n\n\n Rajan, Kaushik Sunder. 2017. Pharmocracy: Value, Politics, and Knowledge in Global Biomedicine<\/em>. Durham: Duke University Press.<\/p>\n\n\n\n Ruckenstein, Minna, and Mika Pantzar. 2017. \u201cBeyond the Quantified Self: Thematic Exploration of a Dataistic Paradigm.\u201d New Media & Society<\/em> 19 (3): 401\u201318. https:\/\/doi.org\/10.1177\/1461444815609081<\/a>.<\/p>\n\n\n\n Ruckenstein, Minna, and Natasha Dow Sch\u00fcll. 2017. \u201cThe Datafication of Health.\u201d Annual Review of Anthropology<\/em> 46 (1): 261\u201378. https:\/\/doi.org\/10.1146\/annurev-anthro-102116-041244<\/a>.<\/p>\n\n\n\n Sch\u00fcll, Natasha Dow. 2016. \u201cData for Life: Wearable Technology and the Design of Self-Care.\u201d BioSocieties<\/em> 11 (3): 317\u201333. https:\/\/doi.org\/10.1057\/biosoc.2015.47<\/a>.<\/p>\n\n\n\n Seabrook, John. 2020. \u201cThe Promise and the Peril of Virtual Health Care.\u201d The New Yorker<\/em>, June 22, 2020. https:\/\/www.newyorker.com\/magazine\/2020\/06\/29\/the-promise-and-the-peril-of-virtual-health-care<\/a>.<\/p>\n\n\n\n Shapiro, Lee. 2020. \u201cLiving With New Realities: The Future Of Virtual Care.\u201d Forbes<\/em>, July 6, 2020. https:\/\/www.forbes.com\/sites\/forbesbusinesscouncil\/2020\/07\/06\/living-with-new-realities-the-future-of-virtual-care\/#5b36a1868c14<\/a>.<\/p>\n\n\n\n Tamminen, Sakari, and Elisabet Holmgren. 2016. \u201cThe Anthropology of Wearables: The Self, The Social, and the Autobiographical.\u201d Ethnographic Praxis in Industry Conference Proceedings<\/em> 2016 (1): 154\u201374. https:\/\/doi.org\/10.1111\/1559-8918.2016.01083<\/a>.<\/p>\n\n\n\n