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Using network science to understand the knowledge exchange pathways in health systems research

University of British Columbia

Evidence-informed public policy has demonstrated positive outcomes for populations. Within the health sector, the concept of evidence-informed decision-making (EIDM) suggests that knowledge generated from scientific research will be translated into evidence to support better policy. To facilitate this process, the concept of knowledge translation (KT) was developed within the Canadian health context fewer than 20 years ago. Achieving the aspirational goals of EIDM and KT has proven difficult. Literature reviews have found that only 20% of knowledge transfer and exchange studies discussed real-world application and 14% of health research findings enter day-to-day practice, taking 17-20 years to do so. New knowledge emerges through collaboration. Many aspects of KT involve complex social processes fundamentally embedded in relationships. There is compelling research showing a group’s success in solving complex problems is primarily correlated with the quality of relationships individuals form. Existing frameworks are almost devoid of interpersonal knowledge exchange (KE) networks and therefore only tell part of the story. Epidemiology has embraced network science for quantitatively describing the transmission dynamics of communicable diseases as a contagion phenomenon. This dissertation uses a similar approach to suggest that KE shares fundamental properties with other contagions. The characteristics of individuals as well as the underlying network structure and heterogeneous patterns of combining and exchanging knowledge translates seamlessly. Two applications are used to support this novel contribution. At the macro- level, a bibliometric analysis is used to understand the international co-authorship trends in health policy and systems research (HPSR). The resulting data were used in a network analysis to understand the degree to which economic regions served by HPSR actually participate. At the micro-level, a survey was conducted in a public health agency with an embedded research mandate. The survey captured demographics, knowledge about research and interpersonal networks on which research knowledge flows. These results were used to show the knowledge exchange pathways within the respective networks. Bibliometric and survey outcomes parameterize scalable, generalizable networks. Both macro- and micro- applications use networks to develop strategies and highlight metrics that facilitate meaningful inclusion of the intended end users throughout the research process to improve KE for EIDM.

Text

2018-08-22

Attribution-NonCommercial-NoDerivatives 4.0 International

http://hdl.handle.net/2429/66888

Resource Management and Environmental Studies

University of British Columbia

UBCV

http://creativecommons.org/licenses/by-nc-nd/4.0/