“Hello, I’m Peter. We haven’t met before but one day you could save my life.”
A few years ago, a young boy spoke these words in a UK advertising campaign for posthumous medical data donation. The campaign, which was sponsored by an organization of medical charities across the country, appealed to the public to consider the benefits that their private health data could yield for future generations.
As medical data goes electronic, and as healthcare systems move toward centralized record systems, medical researchers in different countries are calling upon authorities to put into place mechanisms and regulations that would allow citizens to donate medical data as easily as they can donate organs. (In the U.S., individuals can do the latter when registering to vote or applying for a driver’s license.) But there are many ethical and logistical questions to be answered about data donation. Academic and public scholarship has addressed some of these questions; but this scholarship also, unwittingly, raises others.
Most published work on data donation has been written by medical researchers, who strongly support the practice. (Surprise!) Though their exact agendas vary, these experts tend to share the following perspectives: 1) Medical data donation has many benefits; 2) If you don’t donate your records, you’re killing future generations; and 3) There are a few ethical concerns surrounding data donation, but these are easily resolved.
The first point has some merit. As medical researchers note, many prevalent health conditions such as Alzheimer’s dementia and Parkinson’s disease are under-researched; and if researchers had a means to study interpersonal differences and other data points, they might better understand phenomena related to these conditions. For instance, why does only one individual among two with biological markers develop a condition? How does shift work impact one’s health? Is there a link between vaccines and certain conditions? “Big data” has enormous potential for research questions like these. Other benefits of data donation? It is relatively easy for individuals to donate, and their donation does not depend upon the circumstances of death (unlike organ donation).
The moral arguments for data donation are less convincing, if only because they sound so coercive. For instance, the authors of a recent University of Oxford-funded study claim, “If one receives healthcare, it is only fair to give back.” They also argue, as others have, that authorities need “to nudge less altruistic individuals to act more responsibly and to take on their share of the collective burden of contributing to medical knowledge.” Some have suggested that authorities should toss individual consent altogether to enforce individuals’ moral obligation to benefit society.
The common understanding among medical researchers is that data death leads to “other deaths by setting back medical science.” So, basically, individuals who refuse to donate their data (and policymakers who neglect to create infrastructure to support their doing so) are bad people. And they have blood on their hands—the blood of future patients like Peter.
It’s disturbing that individuals are being made to feel indebted to the medical industry, especially because this industry is the only one guaranteed to benefit from data donation. (Data donation significantly expands researchers’ workload and relevance.) Future patients might benefit, if research yields insights that improve their health-related quality of life. But doesn’t this take for granted that biomedical research is the holy grail?
This may come as a shock to medical researchers, but not all individuals living with chronic conditions want to be cured. Nor do they necessarily desire the growth of medical and scientific knowledge about their conditions.
This may come as a shock to medical researchers, but not all individuals living with chronic conditions want to be cured. Nor do they necessarily desire the growth of medical and scientific knowledge about their conditions. This is because, in some cases, such knowledge does them harm. Take autism, for instance. Some of the above-mentioned researchers tout that big data from patient records enabled researchers to debunk the myth that vaccines cause autism. This particular finding may not concern autistics—but the pathologizing of autism, more generally, does.
Many autistics think of their condition as a way of being, rather than as a biological deficit in need of medical solutions. (This does not mean that they do not recognize the challenges of co-morbidities, such as sensory issues and anxiety.) From these individuals’ perspective, biomedical models of autism are to blame for the cultural attitudes that marginalize autistics. So, it is easy to see why these persons might be reluctant to give more fodder to the institutions that prohibit them from more fully participating in society.
Another concern about biomedical research is this: it directs attention and resources toward the future, while individuals in the present lack basic resources, including life-saving medications and access to quality healthcare. “But it’s not an either/or!” researchers may insist. “Medical researchers can work to improve the health of future generations, while other stakeholders in the health industries focus attention on improving the quality and affordability of healthcare in the present.”
The thing is, there are limited resources to go around, especially when it comes to the patient organizations that fund such initiatives. Diabetes funding provides a useful example. Both of the leading diabetes organizations—American Diabetes Association and the Juvenile Diabetes Research Foundation—pour money into cure research. Meanwhile, a growing number of diabetics cannot afford their insulin, which now costs about $275 a vial in the United States. These inflated costs have led 6,000+ individuals to create GoFundMe pages to pay for this essential medication. Such a scenario evidences why medical research should not be regarded as the be-all and end-all.
Unfortunately, current discussions about data donation fail to appreciate this point; instead, they explore ways to leverage the time and money of state agencies, university laboratories, commercial industries, and more toward this single end.
Medical researchers also downplay the risks and limitations of data donation. They rightly recognize certain risks such as the following: data donation could violate the privacy of the donor if data is not properly anonymized; data could also violate the privacy of living family members; and there is always the possibility of data being used for purposes other than those to which the donor agreed. But there are plenty of other risks that deserve attention. For instance, what conflicts of interest exist when drugmakers are closely involved in research? One medical researcher writing for Scientific American tries to close the door for discussion on this topic, saying, “We should not be afraid that commercial researchers might use the data for ethically approved medical research projects . . . New drugs and devices need the involvement of pharmaceutical and biotech companies.”
But the pharmaceutical industry is known to go in search of diseases for its cures. A notorious example of this involves Eli Lilly and its synthetic human growth hormone (HGH). In 2003, the drugmaker petitioned the FDA for the ability to sell its HGH not only to children who are short as the result of a diagnosable condition, but also to children who fall within the bottom 1.2% of height for their age group. The adjustment increased Lilly’s potential customers by 400,000 and improved annual sales by 40 percent—roughly $130 million—in one year.  Obviously, data donation would facilitate market-expanding activities like this, which have profits and not patients in mind.
There is also very little discussion of the increased risk of biomedical surveillance—government bodies using data to profile and/or impose certain norms on populations. Nor is there any meaningful discussion of the racial and gender politics of this practice, especially with regard to individuals who are understandably reluctant to hand over their health identities to medical experts.
And finally, there isn’t much discussion of the quality or accuracy of individual health records. Patients distort and omit facts, often, with good reason. And some doctors don’t listen very carefully. Both of these realities should be considered when discussing the “gold mine” of patient records.
All of this is to say: conversations about data donation need to be more robust. And those conversations need to include an array of stakeholders, not just medical researchers. A few years ago, a UK organization was created with these exact goals. The not-for-profit “Understanding Patient Data” supports conversations about the use of patient data by increasing transparency, spreading awareness, and giving various stakeholders (including members of the public) opportunities to share insights, express concerns, and shape policies and practices of data donation.
But this organization is the only one of its kind , and it only serves one country. The U.S. and other countries are swiftly moving toward data donation. Public health and social science researchers in these countries need to assemble their own working groups to ensure that data donation and the research it enables do more good than harm to current and future generations. And those working groups also need to discern public attitudes about the extent to which the health industries should invest in data donation. Importantly, this “public” must include individuals with disabilities and chronic conditions, who are arguably the most affected by these practices and policies. Time, money, and brain power spent toward data donation and future-oriented research is time, money, and brain power not spent on the public health concerns of the present.
 See Eli Clare’s Brilliant Imperfection: Grappling With Cure (2017).
 Some patient advocacy groups have made efforts to engage the public in conversations about patient data usage, but these are specific to the groups’ particular interests. They do not raise broader awareness about patient data issues, as UDP does.