Closing the Gap: Translating Information into Policy – Key Observations Drawn Primarily from the Health Sector

Understanding the relationship between research, information, and policy can be challenging. In the health sector, for example, the inter-relationship among the three can be particularly informative for exploring interactions between information and policy development. Discoveries from this area can be applicable to other fields. Traditionally, health was defined narrowly as being attributed to sickness or disease (Riley & de Nazelle, 2019). Health Canada, however, has adopted a broader interpretation established by the World Health Organization. Considering health as “a state of completed physical, mental and social well-being, and not merely the absence of disease or infirmity” (Health Canada, 2008) allows health information to permeate the policy realm with greater breadth and across disciplines than a narrower perspective would support. A definition of health that reflects its complexity helps to make the connections between components clearer and to see how health figures in all relevant policies.

The ways and means by which health information is presented can directly impact how health policy is formulated and interpreted by other related disciplines and within the policy making arena. Institutional structures, communication, collaboration, trust, and local knowledge are key elements contributing to the translation of health information into policy.

Institutional Structures

Incorporating research into policy is both a technical matter and a political challenge. A government’s capacity to develop effective policies is dependent on political systems; whether the structure of the state is centralized or federal, the level of democracy and the role of the bureaucracy affect policy development (Liverani, Hawkins, & Parkhurst, 2013). Understanding is needed of not only decision-making processes—who influences decisions and who makes the decisions—but also, of factors that can influence the decision-making process, such as, what are the trade-offs and what are the implications for budgets and priorities (Liverani, Hawkins, & Parkhurst, 2013). When researchers have an understanding of the policy process, and the contexts in which decisions are made, they are more likely to be able to maximize the influence of the information they have produced and to present policy-relevant information to decision makers (Riley & de Nazelle, 2019).

Capacity, Communication, and Collaboration

Increasing the policy influence of health research requires capacity-building and collaboration (El-Jardali, Lavis, Moat, Pantoja, & Ataya, 2014; Riley & de Nazelle, 2019). Capacity can refer to a number of factors such as organizational design, human resources, financial and infrastructure capabilities, and other resources (Bates et al., 2006; El-Jardali et al., 2014). Ensuring the right people, with the right capabilities, are in the right place, at the right time is a fundamental enabler to closing the gap between health information and evidence-informed health policy. When governments lack the institutional capacity for effective research and information production, ideological and political biases take on greater importance during the policy making process (Liverani, Hawkins, & Parkhurst, 2013). To combat these biases, producers of health information need more than simply the skills to generate high-quality, trustworthy information. They also need to build the capacity to communicate information (El-Jardali et al., 2014) and deliver actionable recommendations (El-Jardali et al., 2014; Riley & de Nazelle, 2019). Effective communication facilitates the translation of evidence to policy with more success than merely generating more information (Marshall et al., 2017).

The impact of health information can be increased through collaboration and interdisciplinary communication. Riley and de Nazelle (2019) highlighted the effect that collaboration between urban planners and health experts has on the creation of well-rounded policy; however, collaboration can also occur between the health sciences and social sciences, and include the production and collection of local knowledge to develop policy recommendations (Yang, 2018).

Trust and Relationships

Information generation is an important component of the decision-making and policy processes. However, the large quantity of information generated every day is one of the barriers to the decision-making processes and “producing more knowledge does not, of itself, lead to greater policy influence” (Marshall et al., 2017, p. 2). To address this hurdle, knowledge must be placed within appropriate contexts and be used to inform policy, not produce it. This point is especially pertinent regarding health information and policies. Therefore, closing the gap between the production of health information and health policy requires robust relationships and trust between knowledge holders, knowledge users, and policymakers. To facilitate strong relationships and trust between groups, the provision of evidence-based health information and messaging from health professionals and organizations is essential (Owusu, Weaver, Yang, Ashley & Popova, 2018). In addition, trust is required to facilitate collaboration between knowledge groups (Song, Temby, Kim, Cisneros & Hickey, 2019).

The use and influence of health information in health policy can be increased through trust in the source of information. Trust (or distrust) in a source can help or hinder the communication of health information. Therefore, it is necessary to ensure evidence-based information is used to inform and shape health policies (Owusu et al., 2018). Furthermore, the characterization of the information environment may affect individuals’ trust in sources of health information and challenge policy interventions (Owusu et al., 2018).

Local Knowledge

Incorporating all three types of knowledge—scientific, social, and local—is important when addressing complex issues such as health related challenges. Local knowledge aims to incorporate local needs and co-produce information to create actionable outcomes that aren’t achievable in isolation. For example, addressing issues related to climate change in the Arctic environment requires both scientific practices as well as incorporating local knowledge by involving indigenous peoples to develop an understanding of the local needs, perspectives, and cultures that is ultimately required to foster effective adaptation planning (Robards et al., 2018).

To make effective decisions, a combination of knowledge types is often required, which is also known as hybrid knowledge (Yang, 2018). When one type of knowledge is overlooked, the performance of public governance and policies can suffer. Collaboration between science, social science, and local knowledge is, therefore, essential to prevent poor public governance and for creating effective policy decisions. For example, policies developed to combat desertification in China that only used scientific information often failed as natural scientists did not fully understand local conditions or ideas about how to resolve local problems (Yang, 2018).

Collaboration between different types of knowledge and increasing the use of local knowledge in policy and decision-making is an essential step to begin closing the gap between information generation and policy production. The diverse research literature we reviewed for this blog post highlighted this point.

Conclusion

The elements that contribute to the effective translation of information into informed policy are not unique to the health sector. Generating trust, building relationships, and communicating relevant, accessible information all contribute to effective navigation of the policy-making processes and increasing the influence of information (Bennett et al., 2017; Liverani, Hawkins, & Parkhurst, 2013; Marshall et al., 2017; Riley & de Nazelle, 2019). Building the capacity of researchers and stakeholders to collaborate in interdisciplinary forums (Alexander et al., 2019; Riley & de Nazelle, 2019), along with establishing strong relationships with decision-makers (El-Jardali et al., 2014; Riley & de Nazelle, 2019) will not only benefit health policy, but also generate a more holistic policy making environment for many subject areas.

References

Alexander, K. A., Hobday, A. J., Cvitanovic, C., Ogier, E., Nash, K. L., Cottrell, R. S., … Watson, R. A. (2019). Progress in integrating natural and social science in marine ecosystem-based management research. Marine and Freshwater Research, 70(1), 71–83. https://doi.org/10.1071/MF17248

Bates, I., Akoto, A. Y. O., Ansong, D., Karikari, P., Bedu-Addo, G., Critchley, J., … Nsiah-Asare, A. (2006). Evaluating health research capacity building: An evidence-based tool. PLoS Medicine, 3(8). https://doi.org/10.1371/journal.pmed.0030299

Bennett, N. J., Roth, R., Klain, S. C., Chan, K., Christie, P., Clark, D. A., … Wyborn, C. (2017). Conservation social science: Understanding and integrating human dimensions to improve conservation. Biological Conservation, 205, 93–108. https://doi.org/10.1016/j.biocon.2016.10.006

El-Jardali, F., Lavis, J., Moat, K., Pantoja, T., & Ataya, N. (2014). Capturing lessons learned from evidence-to-policy initiatives through structured reflection. Health Research Policy and Systems; London,12(2). doi: 0.1186/1478-4505-12-2

Liverani, M., Hawkins, B., & Parkhurst, J. O. (2013). Political and institutional influences on the use of evidence in public health policy. A systematic review.PloS One, 8(10), E77404. doi: 10.1371/journal.pone.0077404

Marshall, N., Adger, N., Attwood, S., Brown, K., Crissman, C., Cvitanovic, C., … Wrigley, D. (2017). Empirically derived guidance for social scientists to influence environmental policy. PLOS ONE, 12(3), e0171950. https://doi.org/10.1371/journal.pone.0171950

Owusu, D., Weaver, S. R., Yang, B., Ashley, D. L., & Popova, L. (2018). Trends in trust in the sources of health information on E-cigarettes among US adults, 2015–2017. American Journal of Public Health, 109(1), 145–147.https://doi.org/10.2105/AJPH.2018.304754

Public Health Agency of Canada. (2008, September 12). What is health? Retrieved from https://www.canada.ca/en/public-health/services/health-promotion/population-health/population-health-approach/what-is-health.html

Riley, R., & de Nazelle, A. (2019). Barriers and enablers of integrating health evidence into transport and urban planning and decision making. In M. Nieuwenhuijsen & H. Khreis (Eds.), Integrating human health into urban and transport planning: A framework(pp. 641–654). Cham: Springer International Publishing. https://doi.org/10.1007/978-3-319-74983-9_31

Robards, M. D., Huntington, H. P., Druckenmiller, M., Lefevre, J., Moses, S. K., Stevenson, Z., … Williams, M. (2018). Understanding and adapting to observed changes in the Alaskan Arctic: Actionable knowledge co-production with Alaska Native communities. Deep Sea Research Part II: Topical Studies in Oceanography, 152, 203–213. https://doi.org/10.1016/j.dsr2.2018.02.008

Song, A.M., Temby, O., Kim, D., Cisneros, A.S., Hickey, G.M. (2019). Measuring, mapping and quantifying the effects of trust and informal communication on transboundary collaboration in the Great Lakes fisheries policy network. Global Environmental Change, 54, 6-18. https://doi.org/10.1016/j.gloenvcha.2018.11.001

Yang, L. (2018). Collaborative knowledge-driven governance: Types and mechanisms of collaboration between science, social science, and local knowledge. Science and Public Policy, 45(1), 53–73. https://doi.org/10.1093/scipol/scx047

 

Authors: Nora Allen, Gillian Curren, and Alison Hurd

 

This blog post is part of a series of posts authored by students in the graduate course “The Role of Information in Public Policy and Decision Making” offered at Dalhousie University.