Doctoral Dissertation Research: The Role of New Data Technologies in the Collaborative Development of Accurate Health Measures

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Comprehensive measures of global population health provide decision-makers with an objective basis for setting health priorities, making cost-effective resource allocation decisions, and assessing the impact of interventions. However, producing accurate measures of global health outcomes is acutely challenging, due to both the lack of quality global health data, and the difficulty of producing universal measures for well-being, cost, and other factors that may vary by region. In recent years, the world's foremost global epidemiology study, the Global Burden of Disease (GBD) Study, has initiated global collaborative efforts to bolster the objectivity and universality of their data and measures. The research supported by this award investigates the grounded micro-practices of these global collaborative efforts in order to understand how global experts use numbers and data technologies to craft scientific consensus and common understandings across cultural contexts. The findings of this research will be disseminated in such a way to aid researchers and policy-makers better understand how large-scale international data collaborations may operate as venues for forging common understandings, negotiating global social goals and projects, and improving the universality and accuracy of health measures. This research uses anthropological methods to investigate the social and technical micro-practices of global collaboration for the GBD study. The researcher will conduct participant observation and interviews with researchers at the institutional home of the GBD study, the Institute for Health Metrics and Evaluation in Seattle, Washington, as well as with their 3,500 global collaborators . The researcher will also conduct historical and semiotic analyses of the quantification procedures used by the GBD study over time in order to evaluate how experts balance scientific, ethical, and social considerations and goals while producing and reviewing health data. In addition to training a graduate student in the methods of social science research, this research will contribute to interdisciplinary efforts to understand the social dynamics of global scientific collaboration and the various ways that social goals and values influence the design and measurement of global health data. Research results will be used to create education materials that will help the public better understand the social and scientific significance and functions of specific measures and data technologies in global health.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.