Can Digital Humanities change the way we study health and practice medicine? How do digital reconfigurations or big data impact and expand investigations into health and medicine's history or trajectory?

  • What Big Data Can't Do: Analog Health and Digital Humanities

    Joel Michael Reynolds's picture
    by Joel Michael Reyn... — The Hastings Center view

    In the Nicomachean Ethics, Aristotle writes, “for what the doctor appears to consider is not even health, but human health, and presumably the health of this human being even more, since he treats one particular patient at a time” (I.6). If Aristotle is right, the aim of medical praxis is ultimately not that of the human, but of singular humans. Despite research in narrative medicine and other forms of patient-centered care confirming the wisdom of Aristotle’s claim, we are today surrounded by arguments and assumptions that the best way to serve individuals is by leveraging knowledge of groups. That is to say, it is in an unparalleled breadth and depth of knowledge about population-level phenomena that Big Data solutions, whether in the service of building biobanks for All of Us™ or leveraging digital health humanities for grant funding streams, ground their promises.

    This is in part due to the fact that medicine, once an art, is today in many respects and in many contexts more akin to a science. There is a constant temptation, more powerful in some domains than others, to envisage the study and application of medicine as best suited to the methodologies and epistemologies of the natural sciences or quantitative social sciences. As with particle physics, would not medical efforts be improved by discovering a grand unified theory—in this case a Grand Unified Theory of Human Health paired with an equally Grand Unified Big Database? Never mind the rabblerousing data on placebo and nocebo effects. Or on health outcomes pertaining to the irremediably qualitative and contextualized issue of patient-provider communication. Or the ever-present concerns about industry influence on data-gathering and peer-reviewed results. If we get all the data we need and tweak our methodologies just right, we will find the True Path to health. But whose health, exactly, will that be? Which particular, singular humans will be better healed, cured, or cared for by following such a path?

    We live in a world where politicians reliably garner votes by ignoring the poor, professing to support the middle class, and ramrodding barefaced legislation to further enrich the 1% amidst one of the largest wealth gaps in the USA’s history. We also live in a world where modern medicine is taken as an achievement that proves humankind’s progress and even enlightenment, whilst nearly half a million people from across the globe died from malaria in 2016. 40 million Americans live in poverty (12% of its population) and 42 individuals hold same wealth as the 3.7 billion poorest in the world. These facts are not unconnected. The NIH’s budget in 2018 is slated to be $36.1 billion. How much scholarly ink will be spilt and public ire raised over which people are served by these funds? And, far more importantly, will this turn to outrage and political action when compared to the over $800 billion dollars that may end up allocated to the department of defense this year alone?

    The intersection of big data and human health will continue to raise hard and complex problems. There is one problem, however, that has and will never be easily solved: how to best judge its unflagging promises. History teaches time and time again that new technologies always appear with new promises to fix old problems or thwart impending ones. As Olivia Banner astutely notes, the type of promises Big Data and its offshoots make are as old (if not older) than the internet itself. We would be wise to heed lessons learned just decades ago.

    One might at this point worry that I have painted too negative of a picture. In a time of gargantuan global inequality, sprawling food deserts, pharmaceutical-company and legislatively-induced epidemics, and other forms of systemic classism, racism, and economic vulturing, there is unquestionably a need for us to better understand population-level phenomenon and to gather more and better data. The digital humanities indeed harbor unique potentials to enrich the ways we practice medicine and study health, especially with respect to the study of its history. As contributors to this question have pointed out, it already has in multiple ways. But let’s not kid ourselves: if Childress and Beauchamp’s principles are still held to be at the core of biomedical ethics, justice is losing the battle in the principled struggle for health for all. No amount of data will decide this ethics fight because principles, values, and their bearers are neither composed of, nor easily persuaded by 0s and 1s.

    I am thus sympathetic with Travis Chi Wing Lau’s warning “to remain critical of the progress narratives attached to ‘Big Data’” and with Jarah Moesch’s worry that the extent to which Big Data solutions focus on altering individual behavior, the moreso such solutions miss the forest for the trees and are liable to reinforce extant stigmas and oppressions. My concern is that digital, technological interventions into what is ultimately an analog, human practice cannot promise to bring about substantive change for those whose lives are least valued and most at risk today. That promise is a promise of justice and of changes to our values, not just our inputs, outputs, or bandwidths. It is with that promise in mind that I hope the humanistic aspect of digital humanities leads the way, for both the USA and the world are in dire need of a more humane sense of health.

  • Lessons on Misreading Digital "Evidence" from the Past

    by Lori Jones — University of Ottawa view

    The Digital Humanities have opened a very wide door into humanity’s medical past. They offer extensive, and often free, online access to digitized disease and medical treatment images, texts, and other materials fromcenturies, if not millennia, ago. They also offer recently digitized “big data” sets of historical disease outbreaks, patient records, and demographic trends, among many other topics. Both of these new points of entry into the past have, in turn, been a huge boon to education, research, and even public outreach in the history of health and medicine. DH has, in short, changed the way that we study health and medicine of the past by allowing more of us to enter the historical world through our computer screens. We can now readily see manuscript images of medieval doctors bleeding their patients or attending to the ubiquitous bent-over haemorrhoid sufferer, of people in the panicked throes of a plague outbreak, and of the Zodiac Man that show us in vivid colour what disease and medicine looked like in the past. We can now easily read first-hand accounts of people’s medical experiences, from both sides of the patient-practitioner divide. And we can now eagerly develop new insights into how historical epidemics appeared in one place after another through databases that can be re-sorted and re-analyzed in multiple different ways. But is it really that simple?

    One of the key limitations of DH is that it has seemingly allowed the otherwise rigorous standards of evidence and interpretation normally applied by historians and scientists alike to be loosened. Online historical medical images typically circulate as cropped versions that have been removed from their original, most often textual, context. The original meanings behind these digitised, cropped, and decontextualised historical images are often lost and, worse, new meanings substituted in their place. Hence, we effortlessly find digital online images of the medieval Black Death that are, in fact, not images of the plague at all.[1] Similar problems arise with the uncritical use of historical data sets. Taking an original data set at face value overlooks potentially critical biases in source collection, selection, interpretation, recording, and even purpose. Re-sorting such databases may generate new insights, but any failure to critique the data sets’ origins and limitations renders such insights suspect.[2] By carelessly using and reusing these images and data sets in our scholarship, we too easily create a distorted view of the past and misinform the present. In other words, we run the risk of undermining our own attempts to produce solid scholarship.

    The Digital Humanities do offer tremendous potential for expanding the nature, quality, and extent of our investigations into the history of health and medicine in new and different ways. But DH also comes with caveats that we have too often ignored. Being aware of these caveats, and carefully heeding the new set of challenges the DH poses to modern scholarship, will help to ensure that DH-based scholarship is not only more interesting and appealing, but also more rigorous and thus valid from historical and scientific standpoints.



    [1]Lori Jones and Richard Nevell, “Plagued by doubt and viral misinformation: the need for evidence-based use of historical disease images,” The Lancet Infectious Diseases 16, no. 10 (October 2016): e235–40. http://dx.doi.org/10.1016/S1473-3099(16)30119-0. Michelle Ziegler, “Lazarus Does Not Have the Plague!” Contagions blog post. 3 January 2018. https://contagions.wordpress.com/2018/01/03/lazarus-does-not-have-the-plague/

    [2]Joris Roosen and Daniel R. Curtis, "Dangers of noncritical use of historical plague data," Emerging Infectious Diseases 24, no. 1 (January 2018), online first 1 December 2017.  https://wwwnc.cdc.gov/eid/article/24/1/17-0477_article. 

     

  • Historicizing Disability and Data: The Promises of DH

    Travis Chi Wing Lau's picture
    by Travis Chi Wing Lau — University of Pennsylvania view

    Disability scholars like Lennard Davis have traced the historical development of the “norm” or average back to the rise of statistics in the nineteenth century.[1] French statistician Adolphe Quetelet, by drawing on astronomical methods for locating stars, theorized the l’homme moyen, a combination of two separate constructions of the human: the l’homme moyen physique (physically average man)and l’homme moyen morale (morally average man). This “average man” was an abstraction composed of the averages of all identifiable human attributes within a state population. As this “norm” characterized the majority of bodies within that population, deviance from that norm became increasingly pathologized as “aberrant” or “abnormal.” The medical and moral imperative to aspire toward normativity ultimately came to underpin eugenic theories and movements in the second half of the century. The later transition to laboratory medicine[2] only further reduced bodies to data produced by laboratory testing procedures informed by principles in the hard sciences.

    Particularly disturbing in this history is the complicity of mathematic and scientific knowledge-making practices in the devaluation of ill or disabled bodies. Advances in testing protocols and techniques have yielded new forms of data collected at the level of tissue, cell, or even molecule. This scalar shift in the understanding of human health and disease bears the promise of greater precision in diagnosis and therapeutic intervention. Yet, as the fields of narrative medicine and bioethics have reminded us, the reduction of individuals to clinical measurements, be it T-cell counts or disease phenotypes, risks dehumanizing patients by disregarding their personal accounts of illness experience. This flattening of patients to data, as I have suggested so far, has a history that needs to be better taught as a part of medical education and reckoned with in practice. We need to remain critical of the progress narratives attached to “Big Data.”

    Critical to empirical knowledge-making is knowing how to read and interpret the data gathered. Digital Humanities can offer a digital literacy informed by humanistic principles of ethics and care that could do better justice to patients navigating the medical establishment, especially those from marginalized populations. One important intervention that Digital Humanities might make in resisting the deterministic overemphasis on quantitative data is a repurposing of “Big Data’s” collection and organizational methodologies toward a medical practice that is structured around the narratives of patients. If “Big Data” tells a very particular story about an individual in specific terms of vital statistics or symptoms, how might we use data-visualization or digital modeling to tell a different story that better witnesses the experiences of the patient? What would a tool like digital medical records look like if it were a visual map of the intersubjective experience between physician and patient during the medical encounter?

    I want to conclude with a recent provocation by Angela Woods about the limits of narrative in medicine[3]. As Woods rightly points out, much of the framework of medical humanities and narrative medicine have relied on a naturalizing of narrative as intrinsic to health and even selfhood. While scholars have begun to call for more critical frameworks for the analysis of illness or disability narratives, what remains mostly unchallenged is the very normativity of narrative itself. I wonder then how Digital Humanities could better attend to forms of nonnarrative communication or provide both patients and medical professionals the means of “framing and communicating their experiences in ways which do not presuppose an orientation towards storytelling or narrative self-presentation.”[4] From a disability perspective, this seems urgently necessary as many disabled individuals may not understand or articulate their experience in conventional narrative forms. Digital Humanities bears the exciting potential to imagine new forms entirely.

    [1]For more on this history, see Lennard Davis. “Constructing Normalcy: The Bell Curve, the Novel, and the Invention of the Disabled Body in the Nineteenth Century.” Enforcing Normalcy: Disability, Deafness, and the Body. New York and London:Verso, 1995.23-72.

    [2]See N.D. Jewson’s “The Disappearance of the Sick-Man from Medical Cosmology, 1770-1870.” Sociology. 10.2 (1976): 225-244.

    [3]Angela Woods. “The limits of narrative: provocations for the medical humanities.” Medical Humanities. 37 (2011): 73-78.

    [4]Ibid. 76. 

  • The Digital Crossroads of Medicine and the Humanities

    Molly Nebiolo's picture
    by Molly Nebiolo — Northeastern University view

    When I reflect on how the digital humanities impact the study of health and medicine, my mind jumps to two points. First, I am reminded of the numerous possibilities the digital world can provide to users around the world. The digital humanities offer efficient communication and proliferation of information that surpasses the speed with which knowledge has been transmitted in the past. Websites like WebMD allow for quick “self-diagnoses” of health problems if someone begins to feel ill. Other more reliable sources of medical knowledge include online courses, digital models, and videos that are available to a universal audience. However, the benefits of the digital platform for studying health are limited to people who have regular access to the internet and who have the skills to navigate it successfully. Through my experience of integrating digital humanities into historical work, I believe the same tenets apply to the ways that digital platforms present health and medicine. These precepts include providing reliable sources to back up statements or presentations, linking other helpful resources the audience may want, and an effective platform for presenting information as clearly as possible.

    Secondly, I think about the ways in which the humanities can improve the investigation and study of medicine through digital means. As Phil Agre notes in “Toward a Critical Technical Practice: Lessons Learned in Trying to Reform AI,” hard science fields, like computer science and medicine, lack the self-critical skills to do historiographical analysis of themselves, which humanists, digital or otherwise, can help address.[1] Kirsten Osthurr notes something similar in her response to this MediaCommons thread by noting, “Now, both of these groups [digital humanist and computer scientists] should join forces with medical humanists to design techniques for better understanding human experiences of illness through big health data.”[2] I agree, and believe a partnership between the humanities and medical fields would produce a rich repository of primary materials for historians of health and medicine. This would provide new knowledge about the trajectories of the public health and medical fields and help science professionals better comprehend social trends and feeling towards medicine. While security restrictions like HIPAA regulate what medical information becomes public, humanists can still contribute to the study and improvement of the health sciences if repositories of medical information are digitally available. Looking ahead to a stronger partnership between the two fields, more critical analysis can assist in bridging the sociocultural boundaries that exist between communities and the health and medical fields. I am thinking specifically about the social discomfort patients have towards doctors, fear or skepticism about westernized treatments, and the overall incredulity Americans have with their health care.

    As a historian of science and medicine, it is fascinating to see how the field of medicine could return to its practical roots because of digital humanities. Medicine and surgery were once trade skills that mothers, neighbors, and butchers practiced. As the field professionalized, these techniques were solidified into one career, that of the doctor. Now, with the availability of digital studying tools open to a wider audience, we could soon see a trend back to a larger community knowing set skills and techniques. The comeback of the midwife is also a prime example of how the influence of the humanities could help with the practice of medicine. There are social reasons why women are avoiding hospitals, which physicians may want to study so they can adapt to cultural needs. With increased availability of open-source data for humanists, albeit information that has been filtered through HIPAA, medical decisions based on social trends can be better understood and attended to in the future. Overall, a relationship between the digital humanities and medicine benefits both audiences of online platforms that educate on health and medicine, and medical scientists who may need a humanistic perspective to better understand the data trends their work is producing.

    ––––-

    [1] Agre, Philip. “Toward a Critical Technical Practice: Lessons Learned in Trying to Reform AI.” Bridging the Great Divide: Social Science, Technical Systems, and Cooperative Work. New York, NY: Psychology Press, 1997.

    [2] Ostherr, Kirsten. “It’s Time for Digital Humanities.” MediaCommons. http://mediacommons.futureofthebook.org/question/can-digital-humanities-change-way-we-study-health-and-practice-medicine-how-do-digital-reco

  • #transform(the underlying systems of digital)health

    Jarah Moesch's picture
    by Jarah Moesch — University of Maryland College Park view

    #transform(the underlying systems of digital)health

    Electronic health records, quantified health, and diagnostic tools are all ‘digital technologies’ that co-create meaning and knowledge throughout the medical industrial complex. The initial connection between digital humanities (DH) and medicine is an easy association to make: DH works with data, with structures of data, with big data, with various forms of tech. Medicine and health are already ‘digital,’ and create and use data and data structures in relationship to various technologies and bodies. Easily, digital humanists can investigate these formations.

    We can also untangle the underlying structures of the U.S. medical industrial complex in order to create new formations founded in justice and care. This is where #transformDH is foundational to the kinds of work that can be done in these intersecting fields. As an academic guerrilla movement invested in transformative scholarship that works for social justice, accessibility, and inclusion, #transformDH’s ideals are exactly what is needed to investigate and change not only how we practice and study medicine and health, but to change the structures of power within the larger medical industrial complex.[1]

    “What counts?" Fiona M Barnett asks, "…what is the effect when the conversation is not about recognizing similarity across differences or disparity in order to build a common ground, but rather, about declaring something to be unrecognizable within the confines of a field?”[2] The U.S. medical industrial complex is founded on preventing difference, on creating normative categories of health, illness, and wellness as well as normative bodies and minds. These structures create invisibility, an inability to recognize “similarity across difference or disparity.”

    To understand how this works, let’s talk “health.” The overarching public health assumption is that the overweight patient is not taking enough personal responsibility, and not following doctor’s orders. The belief is that people are individually responsible for their behaviors
and therefore are at fault if they don’t ‘choose wisely.’  The idea that having a ‘fit’ body somehow prevents disease
 means that individuals must “take responsibility” to continuously monitor and modify their “life style” for health reasons. 
Therefore, it becomes a public health concern to exercise more, 
give up our favorite foods, stop eating sugar, salt, fat, and high fructose corn syrup. The thought is that even though we know we should eat better and get more exercise, 
it is hard to make the transition from having that knowledge and practicing it.[3]⁠  This becomes fact: individuals are somehow always responsible for their failed health or disability.[4]

    Their solution? Give patients fitness trackers and they will somehow miraculously lose weight. Somehow this will motivate people to stop being ‘couch potatoes,’ and hold them responsible for their own health.

    My hypothesis, a #transformDH approach, is different: the use of wearable fitness trackers/activity trackers for medical interventions into “healthy” bodies is unethical.[5] I begin this approach by questioning and dismantling the histories and systems that created and produced the fitness tracker in the first place.[6]

    The Coerced Quantified Self

    In addition to individuals purchasing and using fitness trackers on their own, health insurance companies, employer wellness programs, and small businesses without employee wellness programs have been providing financial incentives and rewards for wearing activity trackers as a way to encourage behavioral changes in activity levels related to overall health, primarily as a way for employers to save money under the guise of individual health improvements.  Many of these programs set expectations for amount of steps and activity needed on a daily basis:  10,000 steps/day and competitions with co-workers are two big ones.

    In reality, these programs collect data for later analysis; they do not automagically change behavior. Essentially corporate and health insurance wellness programs that rely mainly on fitness trackers are running a large experiment to see if trackers actually work to make people more healthy and therefore companies more profitable by reducing health insurance expenditures. This is unethical.

    Some people feel coerced to participate through office pool shaming, where the person who gets most steps wins a prize. Other people have undisclosed illnesses that prevent them from fully engaging, while still others are prescribed medications that cause them to gain weight: the benefit of the medication to the illness outweighs weight gain as a side effect. And finally, many people have physical limitations, and therefore might have difficulties with 10,000 steps per day.

    Should individuals eat fast food, or drink a soda, or not meet the required number of steps for their ‘team’ to win the office health pool, they become individually responsible for all of their ill health, which then can become medical non-compliance, with potentially serious repercussions for clinical treatment. By defining health as an individual behavior it removes responsibility from the community. In doing so, the state begins to legalize morality claims about the choices people make, from the “sin’ taxes on tobacco and alcohol, to the recent attempts to do so with soda and fried foods. These policies are being used as a strategy to control people’s choices, with the hope that this will reduce the “obesity epidemic.”

    However, individual behaviors do not take into account the disparities “in the burden of disease, injury, violence, or opportunities to achieve optimal health that are experienced by socially disadvantaged populations.”⁠[7] These ideologies about health are actually the structural and functional histories of discrimination towards particular bodies to maintain population control.

    By looking at the structures behind the fitness tracker, we understand that mandating wearable fitness trackers for medical interventions into health is unethical. Our focus on the implicit, less recognizable issues within the structures of health care enables us to understand how the system is designed to create unequal care, where access, diagnosis, and treatments vary considerably.⁠[8]This changes how we look at the digital technologies of the fitness tracker. Digital technologies contribute to already existing disparities. Discourses of power and control have real, material consequences.

    A #transformDH approach: looking behind the technology to the larger historical, cultural, and structural foundations extends basic ethics on human subjects outwards 
to include dehumanizing employee data collection with particular pre-set unrealistic standards that have nothing to do with health. 
The combination of individualism, privatization, and profit are not only inappropriate, but violate basic ethical principles.

    While it seems like trackers are all about convincing people to convert personal knowledge about ‘health’ into action, 
it instead is about the acquisition of data points to hold marginalized individuals responsible 
for systemic inequalities against them, 
and therefore enable control over these same populations.  This is violence: from the perspective of a person coerced to use the tracker as part of a corporate wellness program, the trackers become agents of a state that is waging violence against them and their bodies. Therefore, it is coerced experimentation, and reinforces the historical violences of both the medical industrial complex and the state.

    Imagine this: to have healthy bodies, we must move away from the enforced blame on individual choice, and turn to community based health design. We must move from the idea of the individual to community based constellations of care that include creating access to safe, affordable food and water, reliable transportation, safe sidewalks, and real accesible health care.If the community can design the spaces and places they live and work in, healthier people will abound.

     


    [1]"#transformDH is an academic guerrilla movement seeking to (re)define capital-letter Digital Humanities as a force for transformative scholarship by collecting, sharing, and highlighting projects that push at its boundaries and work for social justice, accessibility, and inclusion.” (http://transformdh.org/about-transformdh/)

    [2]Fiona M. Barnett; The Brave Side of Digital Humanities. Differences 1 May 2014; 25 (1): 64–78. https://doi-org.proxy-um.researchport.umd.edu/10.1215/10407391-2420003

    [3]Steve Aldana, Well Steps: Wearables and Wellness: The Complete Guide, June 13, 2016. https://www.wellsteps.com/blog/2016/06/13/wearables-and-wellness-programs/

    [4]Doug Roe, Wearable Concerns: Lifestyle vs. Medical-Grade Devices, Sept 7, 2016 https://www.meddeviceonline.com/doc/wearable-concerns-lifestyle-vs-medical-grade-devices-0001

    [5]See alsoAnne Cong-Huyen’s blog post “#mla13 “Thinking Through Race” Presentation” to understand more about how #transformDH came to be, and explore its founding pricinciples https://anitaconchita.wordpress.com/2013/01/07/mla13-presentation (viewed 1/05/2018)

    [6]"Digital humanists have heard numerous recent calls for the field to interrogate race, gender, and other structures of power,” says Miriam Posner: “to truly engage in this kind of critical work, I contend, would be much more difficult and fascinating than anything we have previously imagined for the future of DH; in fact, it would require dismantling and rebuilding much of the organizing logic that underlies our work." Miriam Posner, What’s Next: The Radical, Unrealized Potential of Digital Humanities, DH Debates, 2016 http://dhdebates.gc.cuny.edu/debates/text/54

    [7] Department of Family Medicine and Community Health, University of Wisconsin http://www.fammed.wisc.edu/aware-medicine/self/

    [8] Department of Family Medicine and Community Health http://www.fammed.wisc.edu/aware-medicine/self/

     

     

  • Automating Fantasies, Past and Present

    Olivia Banner's picture
    by Olivia Banner — University of Texas at Dallas view

    While the rhetoric around today’s big data-driven biomedical endeavors – the Precision Medicine Initiative, the 21st Century Cures Act, the Brain Research through Advancing Innovative Technologies Initiative – posits that our new technologies put us on the cusp of something entirely new, a similar feeling suffused the post-World War II US health care professions. Psychiatrists, like professionals in so many other fields, looked in wonder upon computers and began to imagine a future in which computation’s fantasized efficiency would ease the post-War rise in demand for their services. In the late 1960s multiple psychiatric journals ran special issues dedicated to automation and psychiatry. Bernard Glueck’s opening paper on the topic in Comprehensive Psychiatry, which he had delivered in his presidential address to that year’s American Psychopathological Association convention, began with a grand description of technological progress in human affairs – space travel facilitated by satellite transmissions, the wonders of television – and of explosive growth in information, population, and automation.1

    Next, Glueck considered what automation might hold for psychiatry, a particularly significant concern because explosive population growth, he claimed, had led to an increase in schizophrenia. A novel class of pharmaceuticals had allowed psychiatric patients to be released into the general population, and the new fear, according to Glueck, was that they would have children, what he called “genetic poisoning.” By learning from other industries where computational technologies were already improving efficiency – he cited Wall Street, airline seating, and the insurance industries – psychiatry could surely mirror their successes. A key concern for Glueck was the possibility for nefarious uses of the massive datasets being accumulated throughout various government sectors, but he assured readers this could be mitigated through carefully screening for stability candidates for data management positions. This would happen, he said, by rating certain people according to their honesty, competence, and other measures of stability; then, by entering that data into a program that holds up to 100 variables, “We can develop models of both superior and inferior individuals” (449). Here, late 1960s psychiatry was already dreaming of machine learning, basing its dream in eugenic ideologies.

    Fifty years later we are faced with big data analytics haunted by these past eugenic fantasies. With big data industries’ insistence that calculative methods can increase efficiencies, flag aberrations, create “choice architectures” by which to “nudge” people toward better behavior, and solve the genetic code, big data, while no longer explicitly concerned with “genetic poisoning,” is biopolitical in its aims, working toward “making live” a populace that can fuel late capitalism’s labor force needs.2 Critical humanistic perspectives on big data – already being explored in work by Jasbir Puar, Kelly Fritsch, Nadine Ehlers and Shiloh Krupar, and myself that follows the trail of data and data rhetoric as they construct debilitated populations — view big data as inimicable to projects that seek to develop alternative models of care.3

    One of the Western epistemologies driving big data is that of total transparency, something that Édouard Glissant argues against.4 To combat that goal, we might need, following Glissant, to aim for strategic opacity instead.5 This could mean critical making where particular groups coalesce into data collectives, keeping their knowledge apart from the broader ecosystem of data brokering, or where collectives use methods developed by feminist, Black, and disability health activists to enable communities to care for themselves. Gynepunk Collective might serve as one example, as well as transgender data collectives; experiments in operating systems such as douglass.io, which addresses the intransigent fact that Western data technology is, down to its core, implicated in what Sylvia Wynter has called the coloniality of Truth, might be another.6

    ––––––––

    1Bernard Glueck, “Automation and Social Change,” Comprehensive Psychiatry 8, no. 6 (1967): 441–49.

    2Jasbir K. Puar, The Right to Maim: Debility, Capacity, Disability (Duke University Press, 2017).

    3Puar; Kelly Fritsch, “Gradations of Debility and Capacity: Biocapitalism and the Neoliberalization of Disability Relations,” Canadian Journal of Disability Studies 4, no. 2 (2015): 12–48; Nadine Ehlers and Shiloh Krupar, “‘When Treating Patients Like Criminals Makes Sense’: Medical Hot Spotting, Race, and Debt,” in Subprime Health: Debt and Race in U.S. Medicine (Minneapolis, Minn.: University of Minnesota Press, 2017), 31–54; Olivia Banner, Communicative Biocapitalism: The Voice of the Patient in Digital Health and the Health Humanities (University of Michigan Press, 2017).

    4Édouard Glissant, Poetics of Relation (University of Michigan Press, 1997).

    5The term “strategic opacity” comes from Tyrone S. Palmer, “‘What Feels More Than Feeling?’: Theorizing the Unthinkability of Black Affect,” Critical Ethnic Studies 3, no. 2 (2017): 31–56.

    6Sylvia Wynter, “Unsettling the Coloniality of Being/Power/Truth/Freedom: Towards the Human, after Man, Its Overrepresentation–An Argument,” CR: The New Centennial Review 3, no. 3 (2003): 257–337.

  • It's Time for Digital Medical Humanities

    Kirsten Ostherr's picture
    by Kirsten Ostherr — Rice University view

     

    The digital transformation of industries like banking, travel, and entertainment is old news, leaving many to ponder why healthcare has not yet been similarly disrupted. While change has been slower to come to medicine, digital technologies have nonetheless already opened up new techniques from gene editing to open electronic health records (EHRs) to patient reviews of doctors on Yelp. Inside of clinical spaces, the practice of medicine is now heavily mediated by screens, and outside, the everyday pursuit of health is heavily mediated by devices of quantification. Under these circumstances, almost any behavior or exposure that can be sensed and digitally quantified becomes reframed as a health behavior available for datafication, intervention, and optimization. This emergent digital health ecosystem produces new concepts of health, disease, risk, privacy, surveillance, and care. It also raises questions about what becomes of the human dimensions of suffering and healing in techno-mediated medical systems that pursue scalable clinical augmentation through artificial intelligence, machine learning, and other computational approaches seeking to convert the nuances of human communication and bodily expression into crunchable datasets.   

     

    These conditions produce a field ripe for both humanistic and digital intervention - digital medical humanities. Like the field of critical code studies, this emerging field integrates historical and theoretical frameworks with applied interventions that aim not only to critique, but also to transform their objects of inquiry.

     

    Much work in the medical humanities is premised on the idea that patients’ voices must be better represented to help address structural inequalities that are elided in narrowly biomedical approaches to care. In the era of EHRs, this is both a human problem and a computational problem. While one doctor can listen to one patient at a time, AI can listen to thousands or millions of patients at a time. Though I am skeptical that current Natural Language Processing algorithms are capable of accurately interpreting the subtleties of human communication, I am convinced that significant patterns and revelations could be found if we were capable of “distant reading” the patient narratives buried in healthcare’s big data. It is undoubtedly true that big data analytics need to develop better human contextual sensitivity to produce meaningful results. It is also true that the capacity to interpret personal health data in relation to population-scale data can yield discoveries that benefit patients precisely because they situate the individual in relation to the mass.

    It is worth noting that the field of health informatics already uses many of the techniques adopted by digital humanities, such as data visualization, text mining, data mapping, and web scraping. In the present moment, analysis of big health data needs digital humanities methods and especially, critical insights into the values, ethics, and harms that are often embedded in the seemingly neutral operations of binary code. Digital humanists have learned to collaborate with computer scientists to develop new methods for understanding human history, experience, and cultural production. Now, both of these groups should join forces with medical humanists to design techniques for better understanding human experiences of illness through big health data. Part of this project must entail critical examination and intervention into the design of the very devices that millions of Americans cheerfully wear to quantify our own health and wellbeing. As technologies at the forefront of digital health, wearables promise to deliver grand insights about how exposures and behaviors shape health outcomes. As technologies that also surreptitiously engage in digital profiling, wearables compromise our privacy and autonomy, exploiting us through gender-, racial- and income-based manipulations, ultimately threatening to reproduce harmful patterns of health disparities through the privatization of care. There is a clear opening here for critical insights and creative energy from scholars whose digital interventions can help make medicine more humane, socially just, and equitable. What's more, right now the tech companies are actually listening.

  • Disease and the Digital Humanities

    Dr. Jacob Steere-Williams's picture
    by Dr. Jacob Steere-... — College of Charleston view

    A couple of months ago I gave a paper at The Charleston Conference, an annual meeting geared towards librarians, archivists, and publishers, that once in a while includes a token historian or two. I was on a panel organized by Wiley Blackwell titled “Transforming Research, and your Library,” which focused on problems of selecting archival content for digitization, and on the myriad uses of digital archives by students and scholars. See a write-up here.

    In addition to being called an “end-user” (which I first took as a slur) for the first time, what surprised me most about the questions I received was how unaware the librarians, archivists, and publishers in the audience were about what I was doing with digital archives in the classroom and in my own research.

    I am a historian of public health and epidemic disease, focusing on the nineteenth century and through the lens of Britain and the British Empire. As thematic approaches to interrogating the past, questions of health, disease, and medicine are particularly well-suited to new tools in digital humanities. Disease, of course, is not only a patient-experienced, subjective and narrative event, it is also a spatial, historical, and population level phenomenon, making the use of big data and visual data particularly appealing. There has been something of a groundswell in the history of medicine for integrating digital humanities, given steam most recently by a workshop I attended in 2016 at the National Library of Medicine, titled “Images and Texts in Medical History,” and seen in recent projects by medical historians-cum- digital humanists like Tom Ewing, who has been using visual data and mapping to analyze the Russian flu epidemic of the late nineteenth century.

    My own use of digital tools in analyzing historical and archival texts has revealed two increasingly common axioms of our times; (1) that digital methodologies are best practiced alongside traditional methods of source analysis, and (2) that rather than provide new answers, digital tools are often most helpful to historians in asking new types of questions. Finishing a book on typhoid fever in Victorian Britain, for example, I’ve long known from archival research that the terms “typhoid” and “enteric” were used interchangeably, but unevenly in the nineteenth century, but I wasn’t exactly sure about the broader trends. Designing a Python script using 100 years of “data” from the British Medical Journal and the Lancet, I coded all uses of both terms, and in a minute or so I saw with some clarity the differing uses of the nosological terms in a much more nuanced way than a google Ngram. The finding didn’t exactly answer a historical question—in fact it was confirmatory— that had stumped me using traditional methods, but rather, led to a fascinating new query; why had the term ‘enteric’ been so popular in the British medical press from the 1870s to the 1890s?  

    My latest use of digital tools is perhaps less esoteric, and hints at the kind of transformative ways that the intersection of digital humanities and the history of medicine can have real, tangible effects on public health and the study of disease.

    I’m currently collaborating with an archivist and an epidemiologist to analyze a rare manuscript at the Waring Historical Library. “MSS 292: Report of Cases of Influenza” is a casebook compiled by Dr. J. Mercier Green, Charleston’s Health Officer, in 1918-19. What makes Green’s casebook so remarkable is that it contains ledgers and scraps of paper written by Charleston’s physicians, who sent to Green the names, dates, addresses, and the race of Charlestonians sick with influenza. Historical research on the most significant pandemic in modern global history has tended to focus on mortality (deaths) rather than morbidity (sickness), and on the public representation of the disease in the media—see, for instance, the University of Michigan’s Influenza Encyclopedia.

    For the Charleston Flu Project, we’re admittedly tackling the spread of the epidemic in one U.S. city, but given the remarkably in-depth nature of Green’s manuscript and the ‘data’ therein, our goal is to both digitize the content, which will be useful for historical and genealogical research, and also to build a GIS map to visualize and model flu sickness in Charleston. For practicing epidemiologists such a morbidity model, when combined with existing mortality models as well as genomic sequencing of influenza viruses, has the potential to be at the cutting edge of epidemic preparedness in public health.

    Decades ago historians William McNeill and Alfred Crosby made the cogent argument that disease has been a central actor in historical change, a view so commonplace today that its premise is rarely even debated. Yet new tools in digital humanities are changing the way that we think about disease in the longue durée of human history.

  • Ethics, Findable Patients, and Medical History

    Dr Lisa Smith's picture
    by Dr Lisa Smith — University of Essex view

    Last year, my research into Sir Hans Sloane’s medical catalogues led me to the Hunterian Museum to look at the preserved babies and foetuses that were once in his collection. Although the specimens are three hundred years old and displayed online, special arrangements are required to view them in person; they are stored in areas that cannot be accessed by non-medical researchers, according to the Human Tissue Act (2004). It is not often that an eighteenth-century historian bumps up against modern ethical issues while doing research, but the emergence of several Digital Humanities projects on medical history may encourage us to think about them more.

    There are now a number of database projects that make old medical records more accessible than ever before, ranging from the early modern (1500-1800) period (The Casebooks Project, The Cullen Project, and The Sloane Letters Project) to the modern (1851-1921) Historical Hospital Admissions Records Project. All are freely available online and provide rich insight into topics such as patient experience, family life, diseases, and doctor-patient relationships.

    As the projects deal with the long-dead, they do not need ethics clearance, even though the records contain detailed information about names, places, diseases, and social or kinship networks. (In the case of HHARP, patient names are redacted for records post-1918.) This makes sense historically in that the experience of illness was rarely private, and our modern concept of confidentiality did not exist before the mid-nineteenth century. It was not unusual for interested family or friends to receive updates from a physician on their loved one.

    But a sufferer writing a letter to a physician in the eighteenth century or visiting an astrologer in the sixteenth century could have had no concept of their consultations being made so widely available for anyone to read centuries later. At the time, though, some patients with embarrassing problems might choose to remain anonymous. In an age of linked data, moreover, it is possible to connect some of those long-dead patients with their descendants. With HHARP, the addresses and names make it possible to search across census data and Medical Officer of Health reports. Even pre-census data can present the possibility of traceable families. A descendant of two patients from Sloane’s practice (Elizabeth Newdigate and Abraham Meure) once contacted me after reading an article in which I discuss them—but Sloane’s patients are even more findable now with the database. In the Cullen Letters, a venereal disease sufferer named Alexander Macdonald of Greenock looks a likely candidate for a family tree I found on ancestry.co.uk.

    Does this matter? In her book Family Secrets, Deborah Cohen suggests that we live in an age where historical family secrets are now primarily a way of finding closeness with our ancestors rather than providing a source of shame. Venereal disease in one’s family tree might simply make us chuckle now, but what if—in other cases—the ability to link medical data pointed to an easily-traced modern family’s darker historical secrets, such as sexual abuse?

    Historians have started to take an interest in ethics. Antoon de Baets, for example, draws on human rights law to consider the rights of the living and the dead, particularly with reference to genocide history. His thoughts on disclosure might be particularly pertinent here: what is the balance between public and private interests? Will disclosure of historical facts do harm to the reputation of someone living or dead without providing sufficient public good?

    DH projects in the history of medicine offer much promise, both for understanding health and illness in the past and for genealogists tracing family trees. With so much readily available and connectable data, however, historians need to take more of an interest in thinking about our underpinning ethics, even when we deal with long-dead subjects. This is not to say we should avoid telling difficult stories, rather we need to reflect more carefully on the stories we choose to tell and how we tell them.

  • Hybrid Healthcare: Helpful or Harmful?

    by Dr. Amanda E. Dal... — Salem State University 1 Comment view

    I see digital humanities as how the humanities engage digitally with the world, not just using data to acquire information about the humanities. In today’s Big Data world, medicine, health, and wellness often come to you. Tailored ads on Facebook display pages devoted to in-home workouts. A plethora of apps exist that paradoxically allow you to use your phone to escape the ubiquity of technology’s demands, such as Calm and InsightTimer; the former features soothing images and mantras, and the latter provides meditations tailored to specific needs, including “dealing with addiction” and “emotional healing.”[1] Many hospitals now allow VirtualVisits, wherein patients and providers can essentially FaceTime appointments. While all of these applications are useful for parents of young children, people with disabilities, people with off-hour or overloaded schedules, usw., they all also lack the sensorily rich aspect of in-person, in-nature experience.

    My research focuses on digital social capital, specifically, how diasporas digitally maintain connections with their culture via Facebook, YouTube, and other social media and videosharing platforms. At the core of such research is emotional and cultural sustainability and wellness. People want to know that there are others like them, others who sing, dance, laugh, act in the way that they do, even if the culture is geographically and chronologically distant. However, the methodology can be applied to – and seen in – more broad examinations of the Internet’s role in daily life. The United Kingdom announced in January 2018 that a new Minister of Loneliness would be appointed to help combat an epidemic of staggering proportions. Ceylan Yeginzu writes, “Government research has found that about 200,000 older people in Britain had not had a conversation with a friend or relative in more than a month.”[2] As an example, Yeginzu cites Briton Carol Jenkins’ use of a loneliness-themed Facebook group that provides support, encouragement, and coping mechanisms to members of various ages across the U.K.; ironically, participation in said group has encouraged Jenkins to go outside their home more. The maintenance of social clubs, bowling alleys, and board game nights are a large part of whole-person healthcare, for loneliness can have wide-ranging affects. As the minister’s position develops, social media initiatives should serve as an adjunct to in-person opportunities.

    Lastly, Sherry Turkle, in Reclaiming Conversation: The Power of Talk in a Digital Age (2015), decries the deleterious effects that digital omnipresence can have on various aspects of human interactions. In one instance, she details the societal benefits achieved as a result of recent technological developments, yet cautions that the rising generation of medical professionals, as digital natives, does not know a world where an answer is not Googleable. She cites instructors’ concerns that residents are frequently not adept in interpersonal relations that allow the whole patient to be studied and seen. The book jacket to Reclaiming Conversation notes, “We are forever elsewhere. But to empathize, to grow, to love and be loved, to take the measure of ourselves or another, to fully understand and engage with the world around us, we must be in conversation.” We live in a hybrid world, a world in which life is simultaneously lived and performed online and in person. We must work to maintain homeostasis between today’s way of life and the way that life is when no technology is available.

    [1] “Meditations.” InsightTimer, https://insighttimer.com/meditation-app. Accessed 21 January 2018.

    [2] Yeginzu, Ceylan. “U.K. Appoints a Minister for Loneliness.” The New York Times. 17 January 2018.https://www.nytimes.com/2018/01/17/world/europe/uk-britain-loneliness.html