Investigating Healthcare & Biomedical Research Infrastructure: Directed Reading Group
Co-Directed by: David Ribes and Meg Moldestad
Class members: Beth Dunbar, Tricia Aung, Jalia Evans, Ramya Bhagirathi Subramanian, Brynn Morrison, Cynthia Zhang, Helen Olsen, Nick Reid
ABSTRACT This document summarizes readings, and class discussions, for this DRG focused on biomedical infrastructures.. In this reading group we explored how to investigate infrastructure in the context of healthcare and biomedical research. We covered a breadth of topics, including (but not limited to) medical service provision, biomedical research, health data and analytics, vaccine/drug production and distribution, public health, and healthcare facility built environments. Readings and discussions had a particular focus on inequities built into these systems and what design contributions we might make to improve them. Many, but not all, readings were drawn from the field of Science and Technology Studies (STS).
What is the purpose of this document?
This document is the final product of the Spring-2022 directed research group (DRG) in the Department of Human Centered Design and Engineering (HCDE) at the University of Washington (UW) in Seattle, WA. It is intended to be a resource for individuals interested in healthcare and biomedical research, and includes synopses of readings from our group as well as our thoughts about these readings.
What is a directed research group (DRG)?
DRGs are exploratory spaces within UW’s HCDE department that offer students a wide range of learning and collaboration opportunities, from doing hands-on design work, to assisting with data analysis, to reading and deeply discussing a given topic of interest. While part of HCDE’s curriculum requirements, they are less structured than typical courses and are co-created by faculty and students. As such, they vary in their focus and scope. While largely made up of students from HCDE, DRGs are open to students across UW, and tend to have 5-15 students per group. For more information about DRGs, or to see a list of current and past topics, visit here.
Who created this document and how?
We were a group of eight bachelors, masters, and PhD students in HCDE and Mechanical Engineering with varied backgrounds and interests in biomedicine, healthcare research, population and global health work, and personal experiences with the U.S. healthcare system. We were co-lead by Dr. David Ribes, Associate Professor in HCDE, and Meg Moldestad, PhD student in HCDE. Dr. Ribes is a sociologist of science and technology with a particular focus on investigating research infrastructures in the sciences. Meg is a speech-language pathologist and qualitative analyst with the Department of Veterans Affairs (VA) healthcare system and has experience researching healthcare quality, access, and technologies (e.g., electronic health records). During Spring quarter of 2022, we met once a week for 10 weeks to investigate infrastructure in the context of healthcare and biomedical research. Students rotated as discussion leads throughout the quarter, introducing that week’s readings and facilitating discussion along with the DRG co-leads. We covered a breadth of topics, including medical service provision, biomedical research, health data and analytics, COVID-19 response, public health (U.S. and global), and sexual health.
During our final meeting, each member presented a pre-written summary for the weeks in which they acted as discussion lead, and together we edited these summaries and co-wrote the “in class” section to capture our thoughts and learnings from the quarter. Some people also chose to share their handwritten notes, which are included as images throughout the document.
How is this document structured?
This document is organized chronologically by week of the quarter; each week we explored 1-2 readings by different authors (or multiple book chapters by the same author). First we present the full citation, then a brief summary of the reading(s), and then our in-class observations and thoughts about the readings.
READINGS, SUMMARIES AND COMMENTARIES
Week 1
Clarke AE, Shim JK, Mamo L, Fosket JR, Fishman JR. Biomedicalization: Technoscientific transformations of health, illness, and US biomedicine. American sociological review. 2003 Apr 1:161-94. https://www.jstor.org/stable/pdf/1519765.pdf
In what has become a classic paper, and a forceful argument, sociologists Adele Clarke et al. argue that medicine has transitioned into a new era, characterized more by ‘biomedicalization’ rather than the standby sociological concept of ‘medicalization’. Medicalization, as a concept, refers to that argument that certain issues are not naturally the domain of medicine, but rather that medicine extends itself to and withdraws from new aspects of life. Birthing, for instance, was once the domain of the midwife (amongst others) but eventually became the sphere of medicine. In turn, homosexuality was once pathologized, and, at least in part, medicine has withdrawn here, demedicalizing.
Clarke et al. argue that something new has emerged – they say in the mid-80s – in which medicine on the one hand has become more strongly entangled with biological research, and pharmaceutical corporations on the other, forming the new conglomerate entity of biomedicine. Biomedicalizaiton differs from medicalization in several key ways: extension into health (and not only the pathological), adoption of information technologies (such as medical records, but also areas such as genomics), highly technicalized medical interventions; transformation of bodies/identities.
In class: We used this paper for scene setting, in combination with Bowker et al. (next reading), in order to define half the class topic – biomedicine – while Bowker et al gave us ‘infrastructure’, thus: biomedical infrastructure!
A class member suggested that much of what this paper discusses is often described as ‘neoliberalism’ (which, very briefly means: relying on market mechanisms in matters of public affairs), but that the paper itself did not use the word.
In the context of the paper, there are multiple references to the devolution of responsibility to the self and notions of responsibilization that are tied to concepts of neoliberalism. In thinking about
Bowker GC, Baker K, Millerand F, Ribes D. Toward information infrastructure studies: Ways of knowing in a networked environment. InInternational handbook of internet research 2009 (pp. 97-117). Springer, Dordrecht.
Concrete forms of infrastructure - roads, buildings, ports, communication networks - are typically more visible than abstract forms of infrastructure - protocols, standards, memory, categorization, help desks, data repositories. In this paper, Bowker et al. explore abstract infrastructures (both human and computer), noting their typically background and invisible quality and that they are often performed by undervalued or invisible workers. Using a science and technology studies (STS) approach, which aims to make the invisible more visible in infrastructural work, Bowker et al. explore the role technologies and organizations have in enabling collaborative knowledge work. Noting Leigh Star’s work, the authors note how infrastructure is relational - “the daily work of one person is the infrastructure of another” (pg. 98).
The authors present a model of infrastructure in terms of distributions along the axes of technical/social and global/local (rather than as polar opposites between technical and social). In building cyberinfrastructure, there is no "social" vs "technical"; rather, we need to consider organizational practices, technical infrastructure, and social norms that together allow scientific work/action over space and time. In considering these infrastructural aspects, at a given moment in time do they require primarily social solutions, primarily technical solutions, or a combination of the two? Finally, in tracing what they call “the long now of infrastructure,” Bowker et al. argue that we need to reconsider how we study increasingly complex sociotechnical systems. We need qualitative research that can scale, better forms of multi-modal research, ways to better understand the highly integrated nature of physical infrastructures with social/organizational/cognitive systems, and finally, to be sensitive to how new ways of knowing are spread across information infrastructures.
In class: See Clarke et al., above. Also:
“Infrastructural inversion” and “visible upon breakdown” as methods we can use to inspect infrastructure and combat its tendency to disappear into the background.
From page 94 (PDF page 2), Bowker lists methods to inspect infrastructure. Calls to study infrastructure in STS have engendered methods for making it and associated, emergent roles visible (Edwards, 2003; Karasti & Baker, 2004; Ribes & Baker, 2007): practical methods such as observing during moments of breakdown (Star, 1999) or conceptual methods such as “infrastructural inversion” (Bowker, 1994).
This paper is not about biomedical infrastructures, but we started to connect the Clarke et al. reading/concepts with infrastructure to come up with the following:
Provoked a discussion about ‘dashboards’ in contemporary medical infrastructure development.
Dashboards are ‘hot’ and often considered a silver bullet solution towards using data. They serve as single points of contact to overlook lots of heterogeneous data and materials. But most of them are dead.
We discussed how infrastructural work involves understanding the limitations of social, political and ethical choices.
Infrastructure studies demystify cyberinfrastructure as revolutionary but instead as mundane: forms of practice, routine, distributed cognition associated with knowledge work.
"Infrastructure is an idea, a vision or an ideal, but it is also a practice, a commitment and a long term endeavor." (Ribes, 2006, p. 299)
Week 2
Committee on Population at the National Research Council. 2013. “U.S. Health in International Perspective: Shorter Lives, Poorer Health.” Washington, D.C.: National Academies, January, 1-4. Johnson, Rucker C. 2017. Public Health and Medical Care Systems, Chapter 4, pp. 106-137.
Chapter 4 “Public Health and Medical Care Systems” in “U.S. Health in International Perspective: Shorter Lives, Poorer Health”compares the performance of the U.S. healthcare system versus health systems in other high income countries at tackling morbidity. Despite being a leader in biomedical research, the U.S. is scrutinized for variable access and quality of healthcare. In this chapter, health systems are defined as the “full continuum between public health (population-based services) and medical care (delivered to individual patients).” The authors frame this exploration through three questions: (1) Do public health and medical care systems affect health outcomes? (2) Are U.S. health systems worse than those in other high-income countries? and (3) Do U.S. health systems explain the U.S. health disadvantage? The authors conclude that despite incomplete data, it appears that the U.S. health system has notable shortcomings that are more pervasive than what exists in other high-income countries’ health systems.
(1) Do public health and medical care systems affect health outcomes?
The authors note how population-based public health efforts have resulted in dramatic reductions in preventable diseases and mortality. Universal Health Care (UHC) is particularly associated with improved health outcomes; the U.S. is the only high-income country that does not offer UHC.
(2) Are U.S. health systems worse than those in other high-income countries?
The U.S. healthcare system has shortcomings that are more visible when compared to the healthcare systems of other countries. The U.S. spends more money on healthcare than other countries, but it is unclear whether this has advantages. Public health in the U.S. is fragmented, and the authors cite indicators that suggest that health outcomes in the U.S. may be inferior. This includes poor access to care and health insurance coverage, poor affordability, fewer physician visits and doctors per capita, fewer facilities and beds per capita, and delays in arranging care. Furthermore, the authors illustrate quality of care based on individuals’ clinical outcomes. The authors cite findings that the U.S. is average or better than other countries in attention to clinical detail, patient-centered communication, and planning for hospital discharge. The same study suggests that the U.S. is worse than average on coordinating care, medical errors, and functional information systems.
(3) Do U.S. health systems explain the U.S. health disadvantage?
The authors argue that there is insufficient data to compare health systems cross-nationally, but acknowledge that the U.S. health system is fragmented. It is unclear if weak coordination of care for chronic conditions contributes to a U.S. health disadvantage. There are some factors that the U.S health system cannot explain.
In class: We discussed the article’s role in defining health systems and quality of care, and equity and social determinants of health (SDOH).
It allowed our group entry into U.S. healthcare and public health systems (helped to understand organized healthcare vs. public health vs. research).
We realized that medical care related little to health. Healthcare mattered more in certain aspects and certain population areas.
This article served as an anchor point for understanding health systems.
The U.S. spends the most on healthcare but the care received does not match its spending.
It also introduced the importance of SDOH and how comparatively small medical care provision has a total influence on health in contrast to SDOH and public health measures.
Conrad P. The shifting engines of medicalization. Journal of health and social behavior 46.1 (2005): 3-14.
This piece by Conrad (2005) offered a counter and complementary perspective to the Clarke et al. (2003) we read during Week #1. Peter Conrad has a PhD from BU, taught at Brandeis and is now Emeritus. His background is in medical sociology, qualitative methods, and he’s a seminal scholar on medicalization (2007 book: The Medicalization of Society). One of his last articles tied medicalization to themes of anticipation; fascinating and relevant to our discussion in week 1. He is a sociologist so ties his arguments back to social norms, power relations, and social control - the political and power dynamics in how ‘normal’ is defined and who does the defining
The thesis of this article is that “changes in medicine in the past two decades are altering the medicalization process,” driven by three “engines:” i) biotech; ii) consumers; and, iii) managed care. As Conrad argues, commercial and market interests drive medicine more than medical professional interests, and “the essence of medicalization became the definitional issue.” Medicalization is the act of defining a problem in medical terms (usually as an illness or disorder) and/or using a medical intervention to treat a given “problem.” As distinguishable from Clarke et al., who claim major transformations in the medicalization process, Conrad sees “shifts” by social actors: “Medicalization still doesn’t occur without social actors doing something to make an entity medical, but the engines that are driving medicalization have changed and we need to refocus our sociological eye as the medicalization train moves into the twenty-first century” (pg. 12)
Conrad also talks about “anticipatory medicalization,” which revolves around the expectation of a medical diagnosis or medical outcome; it depends not on a present condition, but rather on putative potential problems. The concept of anticipatory medicalization provides a good example of increasing medicalization - for example, the rise of "preconception care" in medicine, or the idea of caring for non-pregnant women with the purpose of alleviating any risks to pregnancies. Health risks may or may not be visible or detectable, but in the framework of anticipatory medicalization, the clinical concern is about risks that have the potential to become visible or detectable. Finally, anticipatory medicalization refers to measurable forms of risk as well as any demonstrable effects on subjective feelings of risk.
In Class: We spent a lot of time discussing the ways in which this piece compared to the Clarke et al. piece, and honestly had a bit of critique on the more ‘rigid’ mindset of this piece compared to the Clarke from the previous week.
We discussed the distinction between medicalization and biomedicalization across the two pieces, as well as the nature of seeing “shifts” rather than “transformation” in this space.
Neoliberalism came back into the conversation as this piece showed costs with managed care went out of control. Managed care attempts to contain costs, but the freedoms of choices start with the consumer.
We also explored the role of evolving social norms in medicalizing things (e.g., recognition of those who are transgender, “Gender Identify Disorder,” at the same time having to meet diagnosis criteria; psychadelic drugs).
Building on the Viagra case study mentioned in the article, and the more delayed research into a female version of Viagra. (Male viagra first approved in 1998 vs. a female version approved in 2015). Contraceptive research primarily focused on female contraceptives - male contraceptive research more stagnant (both because there is less commercial interest and less basic research in sperm biology).
The increase in the number of media promotions of healthcare were focussed in a manner where individuals were treated more as consumers and not as patients.
We were struck by the limited engagements with questions of class and gender, which tie in explicitly to his discussion of new forms of medical need –
“I would be remiss if I did not note the gendered nature of much corporatized medicalization. This should be no surprise, since women’s bodies have long been objects of medical control”, pg. 11 (this is the only mention of gender in the article).
Week 3
Cambrosio A, Keating P, Schlich T, Weisz G. Regulatory objectivity and the generation and management of evidence in medicine. Social science & medicine. 2006 Jul 1;63(1):189-99.
This article by Cambrosio et al. discusses how objectivity is constructed in western medicine. In the mid-1900's biomedicine "emerged" as a scientific discipline, which like other sciences at the time, was reductive and attempted to systematically organize the practice of medicine. Currently, biomedical knowledge defines the operation of healthcare systems and how medical professionals manage individual patient's health.
Throughout the article, CD-4 counts are used to illustrate how a measurement is classified and aligned with medical practices. These CD categories refer to numbers of antibodies present in a person's blood, for which specific measurements have been made to assess normal and abnormal counts. The CD-4 count is central to the management of the HIV virus and has been actively changed and revised since the start of the HIV epidemic.
When a person living with HIV consults a doctor about their CD-4 count, the doctor uses knowledge about CD-4 to counsel the patient; this knowledge comes from a variety of sources and experiences; we have attempted to draw this relationship below.
In class: We asked ourselves the question, how do we make knowledge “objective?”
Cambrosio et al. point to the vast ‘background’ networks of scientists who go about making decisions about gray-zone issues, but whose decisions are rendered invisible (i.e., objective) downstream. This turns our attention away from doctor-patient interactions, and instead to all the tools and tests the doctor relies on (i.e., infrastructure) and how much work goes into stabilizing those backgrounded tests and tools.
It was a little hard to dig deep into this articlr, particularly in contrast to the other reading this week, Big Med (see below). Not because it is a ‘bad’ article – we liked it and returned to it throughout the class- but because it is highly abstract, almost philosophical, while the Big Med reading was far more grounded, and scene setting.
Dranove D, Burns LR. Big Med: Megaproviders and the High Cost of Health Care in America. University of Chicago Press; 2021 May 25. Chapters: Preface + Intro + Ch. 2 + Ch. 3 + Ch. 5 + Ch. 6.
The chapters in this book focused on the ways that megaproviders are dominating and harming the health economy. A major theme in the book relates to “integrated care” - where integration happens vertically (e.g., primary care to specialty care) and horizontally (e.g., main hospitals with outpatient clinics; hospitals with other hospitals; electronic health records). Megaproviders possess and grow their market power, raising prices and avoiding certain steps to be more efficient. They failed to successfully integrate with physicians, leaving them out of conversations when their decisions are vital to the performance of the entire health system. Burns and Dranove argued that physicians were demoralized and unwilling to work with hospitals to drive change, which led to health system stagnation. A major point of the book is that megaproviders will continue to dominate the health care landscape even if commercial insurance is ended. The book is centered around either eliminating megaproviders or figuring out how to make them work for the people.
The big themes of the book are:
Healthcare is local, and megaproviders have significant power in their local markets; just because something works in one geographic area does not mean it will work in other areas
When hospitals merge based on financial relationships, they concentrate market power, charge higher prices and exclude competitors. These higher prices do not correspond with higher quality of care.
They doubt the concept of effective reform coming from outside the industry and lean towards the belief that the healthcare industry must heal itself.
Integrated health systems continue to grow into megaproviders because of ineffective antitrust enforcement.
This book brings up the concept that the “real” costs of healthcare are related to the “pen” (i.e., doctors deciding what care is needed)
One question we had after reading this was whether this idea was ubiquitous, or specific to the authors of this book?
In class: We discussed Dranove and Burns’ backgrounds in healthcare industry management and their experiences as experts in several antitrust cases against hospital systems. We debated whether their time as witnesses in these cases impacted their attitudes towards megaproviders and the larger healthcare industry. We discussed how the economic vocabulary of the healthcare industry has changed since the 1970s, and spoke at length about our experiences with Kaiser and other hospital systems.
Big Med, and Kaiser more specifically, became returning examples in the class. This book often compares the Northern California Kaiser model to other systems -- as this singular HMO model has been difficult for other US states to replicate (thus furthering the argument that healthcare is local).
Week 4
Veinot TC, Ancker JS, Cole-Lewis H, Mynatt ED, Parker AG, Siek KA, Mamykina L. Leveling up: on the potential of upstream health informatics interventions to enhance health equity. Medical care. 2019 Jun 1;57:S108-14.
Veinot et al. explore the profound “social phenomena'' of health and health disparities through health informatics interventions and what they phenomenally lack. For instance, the authors immediately touch upon the sole focus of health informatics to be on the individual (effort, behavior and choice) which leads to most of these interventions being targeted and ineffective for marginalized groups. Secondly, Veinot et al. provides context that interventions in consumer health informatics are also limited. They tend to reinforce health disparities, which benefit non-marginalized groups who already have health-related advantages.
The goal of the author's piece is to present a “leveled-up” proposal for upstream interventions in informatics, which includes focusing more on healthy equity by using sets of intervention targets and strategies that are more broad. Veinot et al. argue for the greater emphasis on “upstream” interventions focusing on the places in which health is reproduced: political, social, economic, and physical contexts. The interventions are “structural” and “environmental” or “meso-level” and “macro-level” interventions. With the broadness of this approach the authors acknowledge the conceptual difficulties that go into their plans and rebuttal with an emphasis beyond informatics. This is done by incorporating information and communication technologies (ICTs). Veinot et al. takes the WHO model for health informatics and maps the role of ICTs to better expand the model to represent health disparities and social stratification.
The model has four main intervention strategies:
Influence social hierarchies
Reduce exposures
Decrease vulnerability
Preventing unequal consequence of ill health
In class:
We ended up not discussing Veinot et al. as we virtually attended and then discussed Calvin Liang’s dissertation proposal! Calvin is a PhD student in HCDE at UW; visit his website for more info on Calvin’s work.
This was the first week we started digging into sexual health
We debated about the state of sex-ed in the U.S. and how it differed across the world.
Week 5
Lakoff, Andrew. 2017. Unprepared. University of California. Chapters: Intro + Ch. 2 + Ch. 5
Introduction
Lakoff frames this book around the comparison of the Ebola and Zika outbreaks of 2014 and 2016, respectively. The contrast between these two outbreaks points out differences in how threats to public health are categorized and how responses to these threats are operationalized. By articulating how "global health security was cobbled together" (p. 7) this book investigates the infrastructure that promotes public health.
Chapter 2: The Generic Biological Threat
This chapter inspects the history of how the U.S. prepared for biological threats to public health, and how military logistics came to define how public health systems became intertwined. A core problem is that "novel" public health emergencies don't have statistical data that can lead to predicative action -- which leads to ad hoc reactions. Consulting companies took up the mantel of operations research to use simulated games as a way to project and prepare for threats and lobby for government funding.
Chapter 5: A Fragile Assemblage
This chapter focuses on the 2012 H5N1 controversy, in which scientists genetically manipulated the avian flu to create a humanly transmissible strain. This NIH-supported project was part of the U.S. government’s initiative to improve pandemic preparedness. Overall, many of us were spooked when reading these chapters and reflecting on the current COVID-19 pandemic…
In class:
A large part of our discussion was how “simulated games” were used to construct knowledge, and questioning the validity of knowledge from those games.
Nature was never the opponent, rather funding was related to threats of Communisim and Terrorism.
The security state apparatus (for things like preparing and manging terrorism) came to be merged with the planning techniques of public health (e.g., prepaing for pandemics). At high government levels, the distinction between these is faint.
The simulations are only as good as the assumptions that go into them (and often “soft” factors, like humans being politically polarized over mask mandates) don’t go into the simulation models). The purpose of the simulations was to convince - especially the government - to invest in preparatory measures. Simulations were a form of rhetoric and persuasion.
When trying to get the backing of funders and/or government officials, big data don’t have the same rhetorical value as games/etc.
Hoeyer, Klaus. "Data as promise: Reconfiguring Danish public health through personalized medicine." Social studies of science 49.4 (2019): 531-555.
https://journals.sagepub.com/doi/full/10.1177/0306312719858697
Klaus Hoeyer, a professor of Health Services Research at the University of Copenhagen, wrote this very future-focused article about personalized medicine and its potential in the healthcare industry. He wanted to discuss how promissory data interacts with ideas about accountability in public health policies and to look at how intensified data collection affects the timeliness of public health policy. He was concerned that the increased focus on data collection and its promises of future evidence can be used to justify postponing action at the detriment of the individual.
His major concern centered around balancing the individual and greater society. He believes that centralized data collection comes with a lack of informed onset during studies and reduces the individuals that seek care to research participants and data points. He argued that more consideration is needed around how this data is being used by secondary sources, and he believed that data analysts are not concerned enough about the costs of collecting the data that they want to use.
Hoeyer discussed P4 Medicine at length:
Predictive
Preventative
Personalized
Participatory
Hoeyer believes that there is a wider narrative around P4 medicine that is not based on enough evidence. P4 medicine is based on the concept of promissory data - data referring to or used relating to the future. P4 hinges on the current costs of data collection being seen as an investment, guaranteeing future return. Hoeyer argues that data-as-promise is a more politically powerful resource than data-as-evidence.
In Class: We discussed Hoeyer’s skepticism and doubts of proponents of massive data collection and personalized medicine.
Data sourcing, do we have enough data and are we using that in the right ways?
Got angry at idea of data driven decision making
People often don’t use the data they have to actually drive a decision
“Data-driven decision making”
Data fragmentation is a real problem, and it’s interesting how Hoyer discusses Denmark’s relative success
We were left wanting more from Hoeyer - what can we actually do with data now? His critique did not seem to include actionable solutions
Week 6
Jasanoff S. et al. Comparative covid response: crisis, knowledge, politics. Interim Report. 12 January 2021. https://www.ingsa.org/covidtag/covid-19-commentary/jasanoff-schmidt/. Accessed 20 Jan 2021.
This is a collaborative report exploring a comparative approach to understanding elements of the COVID-19 response across 18 countries. The report and its authors were interdisciplinary by design but the theoretical frame and methods employed were grounded in STS. The core findings of the report speak to the critical importance of “pre-existing conditions” in understanding and situating different national responses to the pandemic. The three key conditions outlined by the authors include:
Weak or decentralized public health infrastructure
Economic inequality
Lack of trust in the government (political alienation)
These pre-existing conditions speak to the axes in which the “social compact” within and between countries has been fragmented or lost prior to - and during the pandemic.
The authors also outline, quite early on, five fallacies that played out in the context of the global COVID response. We focused the bulk of our discussion in class on exploring these fallacies and tying them to our previous readings in STS and biomedical infrastructures.
Fallacy 1. A playbook can manage a plague
Fallacy 2. In an emergency, politics take a backseat to policy
Fallacy 3. Indicators of success and failure are clear - and outcomes can be well defined and objectively measured
Fallacy 4. Science advisors enable policymakers to choose the best policies
Fallacy 5. Distrust in public health advice reflects scientific illiteracy
The report itself is quite schematic and details a number of different aspects of STS oriented framing with which the reader can interpret different case studies in COVID response across the 18 countries represented. Ultimately, the authors argue that we need to reimagine the “social compact” in the context of the 21st century.
In Class: This was a simultaneously lively and somewhat disturbing text. It used very colloquial language at times, made wide assertions but without strong evidence, though all from well recognized scholars at premier institutions. In this it was both refreshing, and somewhat curious, bold but also perhaps haphazard. We walked through a number of the schematic points of the article together, including a detailed exploration of the fallacies.
It classified country-level COVID responses according to them being Chaotic (e.g., United States), Consensual (e.g., France, Australia, Austria), or Controlling (e.g., China)
We questioned some of the classifications - for example, Australia had strict lockdown restrictions, flight restrictions, etc., which seemed to fall more into the category of Controlling
Playbook came up - they argue that during a crisis the playbook gets thrown out (one of the fallacies) - we discussed this extensively in class.
Hard Truth #4: A universal “Playbook” is not the answer.
We spoke about how policy makers need to tweak their design of social intervention by accounting for the political contexts they would be set in.
This article focused on the asymmetries between technology and political infrastructure in the healthcare domain, specifically in the field of Precision Medicine and in the context of the COVID-19 pandemic. Precision medicine is the utilization of molecular data as a basis of clinical diagnosis and practice. The resources used in Precision Medicine caused an increase in the new biotech era by using expensive molecular labs. This field of Precision Medicine is an example of political viability in the making of science, technology, and innovation (ST&I) agendas in health. The new research infrastructure created the path for international research on non-transmissible chronic, genetic and autoimmune diseases. (Pg. 2)
Though there is a noticeable increase in the supply of qualified scientific and technology knowledge in health and biomedical sciences, the translation of the knowledge to public health systems is flawed and inefficient. The authors focused on uncovering the gap in translating knowledge and technologies into coordinated responses to the COVID-19 pandemic. The authors attempted to show the correlation between Implementation Science (IS), Precision Medicine (PM) and Precision Public Health (PPH) to strengthen the technology, science, and learning between them. As they argue, this can help advance the academic space. There is a need for a relevant role of policy makers in integrating science, technology, and policy with the public healthcare system’s planning and policies.
To improve the governance of ST&I for public health needs as a post pandemic outcome, the authors noted the need for efficient tools of governance to enable multi directional flow of knowledge through academic, business and clinical environments. The authors concluded by speaking about how translating Precision Medicine infrastructure to Public Health needs is a difficult change. Since Precision Medicine has its focus on the design of technology and solutions to the problems in public and private healthcare, it can burden the financial sustainability of health systems worldwide. It can increase the inequality in access to health, as some countries may be better positioned to adapt to the newer standards and modern advances may not be applied to all populations equally. Future preparedness assessment reports and panels must be institutionalized by health systems and articulated alongside academia and the health industry.
In class:
We discussed the ideas presented in the paper that the solution is in the future, and how we can access it by collecting data now and figuring it out later.
We found this “future-thinking” only seemed to further the inequality argument; we again returned to the idea of neoliberalism as a force that does not actually serve public health needs.
It cited the Jasanoff article, but we found that it actually missed the point Jasanoff was making; i.e., precision medicine is not actually doable or a positive force in improving public health.
Week 7
Silva HP, Lehoux P, Miller FA. Introducing responsible innovation in health: a policy-oriented framework. Health Res Policy Sys. 2018. https://doi.org/10.1186/s12961-018-0362-5.
Through this paper we learned about the current frameworks in the Innovation of Health and how they are inequitable and unsustainable. The author aimed to introduce the RIH (Responsible Innovation in Health) Framework to iteratively modify the work of people who supply Health Innovation. The author noted that the principles, values and requirements of the framework are considered throughout the innovation lifecycle. The RIH framework adopts a global perspective on health systems. It articulates issues throughout the health innovation development process. It responds to the crucial need to provide health and innovation policy makers with a common framework. The RIH framework emphasizes dimensions in the fields of:
Population Health
Health Systems
Economic Systems
Organizational Systems
Environmental Systems
The authors compared the RIH framework with the existing RRI framework (Responsible Research and Innovation). The authors also spoke about how the RRI framework differs between the Product and Process approach while creating products and services in the health innovation sphere. RRI is the emphasis on what society morally desires to achieve, on the socioeconomic benefits of innovation and on a closer collaboration with industry. The authors spoke about the the risk of using RRI that can lead to “intellectual neo-colonisation” if its application to the developing world reproduces or reinforces problematic relations. (Pg.10) RIH, purportedly in contrast, is an ambitious and sustained effort that requires collaboration among many diverse stakeholder groups. Although RIH cannot be directly adapted to certain countries, it was developed with the notion that many established technologies are too expensive with existing resources in certain regions.
In class: We were critical of this paper’s claim to making a model that was more encompassing than previous models, while seeming almost too broad to be useful. In addition:
Notably, there was nothing in the framework about triggering feedback, which we critiqued as a crucial missing part of the diagram (see below).
We talked about how innovation is rarely linear.
We criticized how having yet another framework that was working towards the betterment of the future and not solving any/most of the existing problems in the domain of biomedicalization may not directly help the healthcare industry.
Swan, J., Goussevskaia, A., Newell, S., Robertson, M., Bresnen, M., & Obembe, A. (2007). Modes of organizing biomedical innovation in the UK and US and the role of integrative and relational capabilities. Research Policy, 36(4), 529-547.
This paper outlined a qualitative analysis comparing biomedical innovation in the U.K. and U.S. The study focuses on these two countries given previous work that outlines how they are different and that the U.S. context better facilitates biomedical innovation. Biomedical innovation is defined as “a process involving the creation and application of scientific and technological knowledge to improve the delivery of human healthcare and the treatment of disease.” The U.S. institutional context may better facilitate R&D linkages between public and private sectors. The U.S. has stronger linkages between industry and universities compared to those in the U.K.
This was a three year study aimed at identifying factors facilitating and impeding innovation projects across U.K .and U.S. contexts. The authors conducted in-depth interviews and longitudinal case studies of innovation projects. Between the two contexts, there are distinct “integrative capabilities” and “relational capabilities.” Integrative capabilities are defined as actions to facilitate the translation of basic research to commercial applications through movement of scientists and their labor market mobility. Relational capabilities are actions that support collaborative product development projects among industry and academia. The authors plot case studies based on two concepts: “organizational coupling” and “knowledge boundaries,” which are used to characterize innovation. Organizational couling is defined as “the organization and management of collaborations and network ties between partners.” Knowledge boundaries are defined as “ways in which knowledge was combined across the different specialist domains involved.”
In class: we discussed the culture of academia/industry in the U.K. and the U.S., which might influence why researchers in the U.S. have more interest in pursuing commercialization. There was confusion on how the authors describe macro-level capabilities and micro-level innovation.
This seemed to cast the U.S. in a more positive light than other papers we read, and that commercialization is not inherently bad and contributes to the integrative nature of our research culture.
This sparked a conversation about the different conceptions of “integration” within biomedicine/biomedical research:
Big Med: vertical/horizontal market integration
Clarke et al.: information technologies (tech integration)
This paper: sector integration, eg., government, industry, academia
Week 8
Adams V. Metrics: What counts in global health. Duke University Press; 2016 Feb 25. Chapters: Intro + Ch. 1 + Ch. 9.
Adams is a medical anthropologist at UCSF and uses this lens to understand and critique the space of global health metrics. Adams’s main point is that metrics are not neutral and instead are political. Page 225 summarizes her argument well:
Metrics enable certain kinds of medical practice while impeding others. They generate forms of knowledge and certainty about some things even while effacing others. They can authorize new kinds of fiscal investments in health, and new ways of linking market models to health care provision… thus even when metrics are changing the terms and conditions of what constitutes health in relation to governance, politics and markets.
Global health planners see that world diseases are in motion without regard to borders constantly trying to overlay interventions. In chapter 1, Adams outlines how universal standards emerge as a tool for colonial and post-colonial rule to stabilize randomness. These metics assume unity of purpose and desires, and as such are not value neutral. Chapter 9 is a case study of a Haitian NGO noting their difficulties quantifying trust, relationship building, and getting donor funding. The data that is counted is fed to USAID where data is generated with outside authorities in mind. Adams ends by advocating for “slow research” with more storytelling and qualitative methods.
In class:
Ethnography as cultural extraction:
We discussed how one limitation of doing ethnographic work is donor funded/grant based nature of research being on short cycles.
“Quantoids” who push mixed methods that are heavy in quantification with tiny qual. (e.g., QUANT qual QUANT)
Quantoids doing less rigorous qualitative research, and also need to operate in the context of grant deadlines.
Development of the DALY by the World Bank to quantify life in terms of potential economic productivity and as a measure for comparing across geographic borders, ignoring any cultural lived experiences of how disease affects an individual, their family, and community. “The DALY also solved a perhaps more important problem for policymakers: how to think about allocation of resources in ways that were, in their terms, ‘value neutral.’”
Duke Press (the publisher of this book) often publishes wilder books and ideas.
RCTs as infrastructural inversion (i.e., help make the invisible visible); visibility = extreme quantification:
“By being ostensibly excluded from the regimes of truth making that are tied to mathematical figuring, stories are left to carry a nonneutral moral certainty that mathematics and RCTs claim deliberately and victoriously to avoid but are, in fact, haunted by as a spectral display that they need.”
We also mapped the history of global health (see image below) in response to the lack of a coherent story within the reading:
We weren’t entirely sure what Adams was advocating for in the end; e.g., what is “slow research?” It had an “us” (anthro/ethnography) vs. “them” (quant/RCT) tone, somewhat reactionary, rather than advocating the value in taking from both, ideally together, rather than in competition or opposition.
Week 9
Epstein, Steven. The Quest for Sexual Health: How an Elusive Ideal Has Transformed Science, Politics, and Everyday Life. First, University of Chicago Press, 2022. Chapters: Intro + Ch. 1 + Ch. 4 + Conclusion.
“What is sexual health?” That is the (very big) question this book strives to answer. Although many organizations have initiated large movements and invested huge amounts of resources to promote what they consider to be a progression towards better sexual health, there seems to be no professional definition or common consensus on what exactly sexual health is.
Epstein notes that rather than delineating sexual health as its own category of health independent of other health issues, perhaps sexual health currently represents more of an umbrella category under which everything falls. For example, it includes everything from physical dysfunctions to the question of the morality of abortion. Epstein strives to explore these questions thoroughly by discussing them through his book.
In class: we discussed our thoughts on what sexual health might be, how it might be later defined in the future, and the current state of the medical industry regarding the topic.
We talked about how the author looks at sexual health as a process not an outcome.
We ended our discussion with the idea that:
We still don’t know what sexual health is and,
Reading the Conclusion first would have helped us have a better idea of what the book was going to be about.
Week 10
We co-wrote this document synchronously in Google Docs.
Other works cited
Ribes, D. Universal informatics: Building cyberinfrastructure, interoperating the geosciences. University of California, San Diego, 2006.