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- All Subjects: Science and Technology Policy
- All Subjects: Biomedical Technology
- Creators: Sarewitz, Daniel
Description
Each of the three essays in this dissertation examine an aspect of health or health care in society. Areas explored within this dissertation include health care as a public value, proscriptive genomic policies, and socio-technical futures of the human lifespan. The first essay explores different forms of health care systems and attempts to understand who believes access to health care is a public value. Using a survey of more than 2,000 U.S. citizens, this study presents statistically significant empirical evidence regarding values and other attributes that predict the probability of individuals within age-based cohorts identifying access to health care as a public value. In the second essay, a menu of policy recommendations for federal regulators is proposed in order to address the lack of uniformity in current state laws concerning genetic information. The policy recommendations consider genetic information as property, privacy protections for re-identifying de-identified genomic information, the establishment of guidelines for law enforcement agencies to access nonforensic databases in criminal investigations, and anti-piracy protections for individuals and their genetic information. The third and final essay explores the socio-technical artifacts of the current health care system for documenting both life and death to understand the potential for altering the future of insurance, the health care delivery system, and individual health outcomes. Through the development of a complex scenario, this essay explores the long-term socio-technical futures of implementing a technology that continuously collects and stores genetic, environmental, and social information from life to death of individual participants.
ContributorsWade, Nathaniel Lane (Author) / Bozeman, Barry (Thesis advisor) / Sarewitz, Daniel (Committee member) / Cook-Deegan, Robert (Committee member) / Arizona State University (Publisher)
Created2019
Description
Atrial fibrillation (AF) is the most common abnormal heart rhythm, affecting
nearly 2% of the world’s population at a cost of $26 Billion in the United States annually, and incalculable costs worldwide. AF causes no symptoms for some people. However, others with AF experience uncomfortable symptoms including palpitations, breathlessness, dizziness, and fatigue. AF can severely diminish quality of life for both AF sufferers and their loved ones. Beyond uncomfortable symptoms, AF is also linked to congestive heart failure and stroke, both of which can cause premature death. Medications often fail to control AF, leading patients and healthcare providers to seek other cures, including catheter ablation. To date, catheter ablation has yielded uneven results, but garners much attention in research and innovation in pursuit of a cure for AF. This dissertation examines the historical development and contemporary practices of AF ablation to identify opportunities to improve the innovation system for the disease. First, I trace the history of AF and AF ablation knowledge from the 2nd century B.C.E. through the present. This historical look identifies patterns of knowledge co-development between science, technology, and technique, as well as publication patterns impacting knowledge dissemination. Second, I examine the current practices of AF ablation knowledge translation from the perspective of clinical practitioners to characterize the demand-side of knowledge translation in real-world practice. Demand-side knowledge translation occurs in nested patterns, and requires data, experience, and trust in order to incorporate knowledge into a practice paradigm. Third, I use social network mapping and analysis to represent the full AF ablation knowledge-practice system and identify
opportunities to modify research and innovation practice in AF ablation based on i
measures of centrality and power. Finally, I outline six linked recommendations using raw data capture during ablation procedures and open big data analytics, coupled with multi-stakeholder social networking approaches, to maximize innovation potential in AF ablation research and practice.
nearly 2% of the world’s population at a cost of $26 Billion in the United States annually, and incalculable costs worldwide. AF causes no symptoms for some people. However, others with AF experience uncomfortable symptoms including palpitations, breathlessness, dizziness, and fatigue. AF can severely diminish quality of life for both AF sufferers and their loved ones. Beyond uncomfortable symptoms, AF is also linked to congestive heart failure and stroke, both of which can cause premature death. Medications often fail to control AF, leading patients and healthcare providers to seek other cures, including catheter ablation. To date, catheter ablation has yielded uneven results, but garners much attention in research and innovation in pursuit of a cure for AF. This dissertation examines the historical development and contemporary practices of AF ablation to identify opportunities to improve the innovation system for the disease. First, I trace the history of AF and AF ablation knowledge from the 2nd century B.C.E. through the present. This historical look identifies patterns of knowledge co-development between science, technology, and technique, as well as publication patterns impacting knowledge dissemination. Second, I examine the current practices of AF ablation knowledge translation from the perspective of clinical practitioners to characterize the demand-side of knowledge translation in real-world practice. Demand-side knowledge translation occurs in nested patterns, and requires data, experience, and trust in order to incorporate knowledge into a practice paradigm. Third, I use social network mapping and analysis to represent the full AF ablation knowledge-practice system and identify
opportunities to modify research and innovation practice in AF ablation based on i
measures of centrality and power. Finally, I outline six linked recommendations using raw data capture during ablation procedures and open big data analytics, coupled with multi-stakeholder social networking approaches, to maximize innovation potential in AF ablation research and practice.
ContributorsRoss, Heather M (Author) / Hackett, Edward J (Thesis advisor) / Hurlbut, James B (Thesis advisor) / Sarewitz, Daniel (Committee member) / Miller, Clark A. (Committee member) / Arizona State University (Publisher)
Created2016
Description
Investments in climate science come with an expectation of social benefit. Science policy--decision processes through which individuals and organizations support, manage, and evaluate research--plays an important role in determining those outcomes. Yet the details of how climate science policy actually works have received very little attention amid academic and policy-focused discussions of climate science. This dissertation examines climate science policy with particular attention to how it supports "public values" that justify research investments. It is widely recognized funding for climate science in the US has advanced knowledge considerably in recent decades but failed to produce useful information for decision makers. In Chapter 2, I use a methodological approach known as Public Value Mapping (PVM) to investigate this failure of the science policy system. My results show that science funding institutions have been ineffective at guiding climate science toward desired outcomes because of problematic, but common assumptions about the links between science and societal benefit. The remaining chapters look more closely at the implications of these tacit assumptions, which are held by individuals, and embedded in the organizations that implement climate science policy. Chapter 3 examines the notion that prediction is essential to climate science. Wide acceptance of the "prediction imperative" limits the scope of climate science policy. Chapter 4 examines the interplay of values and assumptions in two recently established organizations in Australia, each supporting research on climate change adaptation. In Chapter 5 I document a widespread assumption in the climate science literature that agreement among multiple models should bolster confidence in their results. This can only be correct if the models are independent of one another. Climate scientists have not demonstrated this to be true, nor have they offered a plausible framework for doing so. This dissertation adds an important dimension to our understanding of how climate science knowledge is produced, while offering constructive and practical recommendations to science policy decision makers working in government programs that fund climate science. Insight from these chapters suggests that an explicit and reflexive focus on values in science policy can be helpful to organizations pursuing science policy innovation.
ContributorsMeyer, Ryan McLaren (Author) / Sarewitz, Daniel (Thesis advisor) / David, Guston (Committee member) / Andrew, Hamilton (Committee member) / Clark, Miller (Committee member) / Roger, Pielke Jr (Committee member) / Arizona State University (Publisher)
Created2010