Faculty Bibliography

As the era of big data transforms modern medicine, clinicians have access to more health data than ever. How do medical providers determine which data are relevant to patient care, which are irrelevant, and which may be inappropriately used to justify potentially harmful interventions? One of the most prominent medical fields to address these questions head on - clinical genomics - is actively debating how to assess the value of genomic data. In-depth interviews with clinicians and a content analysis of policy documents demonstrate that while many clinicians believe that collecting as much patient data as possible will lead to better patient care, a sizeable minority of clinicians preferred to collect less data. These clinicians worried that large genomic tests provided too much data, leading to confusion and inappropriate treatment. Clinical geneticists have also started developing the concept of "actionability" to assess which types of genomic data are worth collecting and interpreting. By classifying data as useful when it can or should lead to action, clinicians can formalize and institutionalize what types of data should be ignored. But achieving consensus about what counts as "actionable" has proven difficult and highlights the different values and risk philosophies of clinicians. At the same time, many clinicians are fighting against the ignorance arising from genomic databases predominantly filled with samples from European ancestry populations. Debates about how and when to institutionalize ignorance of health data are not unique to clinical genomics, but have spread throughout many fields of medicine. As the amount of health data available to clinicians and patients grows, social science research on the politics of knowledge and ignorance should inform debates about the value of data in medicine.

In modern medicine, health risks are often managed through the collection of health data and subsequent intervention. One of the goals of clinical genetics, for example, is to identify genetic predisposition to disease so that individuals can intervene to prevent potential harms. But recently, some clinicians have suggested that patients should undergo less testing and monitoring in an effort to reduce overdiagnosis and overtreatment. In this paper, I explore how clinicians navigate the tension between identifying real disease risks for their patients with concerns about overdiagnosis and overtreatment. I focus on clinicians ordering genetic testing for inherited cardiovascular diseases. Of the genes determined to be "clinically actionable" by the American College of Medical Genetics and Genomics (ACMG), half are related to cardiovascular diseases. But, due in part to high levels of uncertainty surrounding cardiovascular genetics, there is still disagreement within the field about how to order and interpret these tests. Based on semi-structured, in-depth interviews with 20 clinicians who order genetic testing for cardiovascular diseases, I find that there is considerable variability in the ways that clinicians determine which types of genetic tests are appropriate for their patients and how they interpret test results. Most importantly, I find that many providers do not presume that more genetic data will lead to better care. Instead, increased genetic data can lead to confusion and inappropriate treatment. This re-valuation of the utility of medical data is crucial for bioethicists to explore, especially as medical fields are sorting through increasing amounts of data.

As maternal mortality increases in the United States, birth providers and policymakers are seeking new solutions to address what scholars have called the "C-section epidemic." Hospital cesarean rates vary tremendously, from 7 to 70 percent of all births. Based on in-depth, semi-structured interviews with 47 obstetricians and family physicians in the United States, I explore one reason for this variation: differences in how physicians perceive and manage risk in American obstetrics. While the dominant model of risk management encourages high levels of intervention and monitoring, I argue that a significant portion of physicians are concerned about high intervention rates in childbirth and are working to reduce cesarean rates and/or the use of monitoring technologies like continuous fetal heart rate monitors. Unlike prior theories of biomedicalization, which suggest that health risks are managed through increased monitoring and intervention, I find that many physicians are resisting this model of risk management by ordering fewer interventions and collecting less information about their patients. These providers acknowledge that interventions designed to mitigate risks may only provide an illusion of control, rather than an actual mastery of risks. By limiting interventions, providers may lose this illusion of control but also mitigate the iatrogenic effects of intervention and continuous monitoring. This alternative approach to risk management is growing in many medical fields and deserves more attention from medical sociologists.

Nearly four in ten American use complementary or alternative medicine (CAM) each year. Even with a large number of patients, CAM practitioners face scrutiny from physicians and biomedical researchers who, in an era of evidence-based medicine, argue there is little evidence to support CAM treatments. Examining how CAM has or has not been integrated into American health care is crucial in understanding the contemporary boundaries of healthcare systems. An analytical tool from science and technology studies, boundary objects, can help scholars of medicine understand which practices become integrated into these systems. Using a comparative analysis based on archival and interview data, this paper examines the use of boundary objects in two alternative medical practices - acupuncture and Christian Science. While boundary objects alone cannot explain what health practices succeed or fail, juxtaposing the use of boundary objects by different CAM groups identifies the work boundary objects do to facilitate integration and the conditions under which they "work." I find that acupuncturists' use of sterile needles as a boundary objects assists in their effective integration into U.S. healthcare because needles are both a symbol of biomedical prowess and a potentially unsafe device requiring regulation. Christian Scientists' use of the placebo effect as a boundary object has not succeeded because they fail to acknowledge the different contextual definitions of the placebo effect in biomedical communities. This comparative analysis highlights how context affects which boundary objects "work" for CAM practices and theorizes why alternative health practices succeed or fail to become integrated into healthcare systems.