Abstract
Through an interpretive, social constructivist approach, the research explores the production and use of information in the public health care domain of a low and middle-income country (LMIC). The research shows that taking action for health is as much about finding ways to deal with various forms of uncertainty or incomplete certainty as it is about producing better and more data.
Theoretically, the research considers the relationship between Information Systems (IS) and knowing. This is a long-standing yet contemporary theme in IS research and development as new enhancements in data-producing technologies stimulate an increasing demand for data globally, for example reflected in the debates around big data. Concepts from the domains of sociology of science and technology and from medical anthropology are drawn into the IS and HIS domain to develop a theoretical lens that takes into account the diverse contextual, situated and material character of how health workers and managers acquire knowledge and take action in the process of providing and administering care in the context of disease surveillance and response. These processes are conceptualized as multiple, cross-disciplinary, epistemic practices where uncertainty plays a key role.
Empirically, the thesis explores how information about the detection and transmission of two diseases (meningitis and dengue) are represented and acted upon in the context of disease surveillance and response in Burkina Faso. The ethnographically inspired case study of data use practices in the domain of disease surveillance and response in the health sector of Burkina Faso explores how health managers and workers create and use health information for the purpose of preventing and controlling contagious diseases. The study highlights how their work includes accounting for, rather than avoiding, different types of uncertainty.
The contributions of the thesis lie both in the sociological conceptualization of how knowledge about a disease is produced and used in the context of disease surveillance and response as well as in the articulation of different aspects of uncertainty and their relation to the understanding of how we know about a disease.
The articulation of uncertainty as not just a barrier to knowing but also a driver of action, helps supplement IS and HIS theory concerned with knowing. Uncertainty is introduced as something that should be considered an important element to action rather than an element that must be avoided and eliminated through the formal IS or HIS. In this sense the findings invite us to flip the context for IS research and reflect further on what IS research can learn from LMICs instead of narrowly focusing on what we as IS researchers and practitioners can bring to this context.