Using Knowledge Brokering to Promote Evidence-Based Policy-Making: The Need for Support structures/Promotion De L'elaboration Des Politiques Sur la Base D'elements Factuels Grace a la Transmission Du Savoir: Necessite De Structures De soutien/Tecnicas De Mediacion De Conocimientos Para Promover la Formulacion De Politicas Basadas En la Evidencia: Necesidad De Estructuras De Apoyo

Introduction Health research and policy-making operate under different settings, each with its own professional culture, resources, imperatives and time frames. For example, policy-makers rarely convey clear messages about the policy challenges they face in their specific context to allow for timely and appropriate research agendas. Researchers on the other hand often produce scientific evidence which is not always tailor-made for application in different contexts and is usually characterized by complexity and grades of uncertainty. (1) Thus, initiatives are needed to facilitate interaction between researchers and policy-makers to foster greater use of research findings and evidence in policy-making and to narrow the (Fig. 1). [FIGURE 1 OMITTED] In 1997, the Canadian Health Services Research Foundation recognized the lack of familiarity between the world of research and that of policy-makers as a major barrier for linking research to policy-making. (2) Jonathan Lomas and the Foundation pioneered knowledge brokering as an approach to foster evidence-informed decision-making. (3,4) Knowledge brokering differs from other strategies, such as researcher push or policy-maker--pull, designed to close the know--do gap. It starts with the recognition that creating knowledge and formulating policy are two different processes. The focus of knowledge brokering is not on transferring of the results of research, but on organizing the interactive process between the producers (researchers) and users (policy-makers) of knowledge (Box 1) so that they can co-produce feasible and research-informed policy options. Knowledge brokering is a two-way process that aims to (1) encourage policy-makers to be more responsive to research findings, and (2) stimulate researchers to conduct policy-relevant research and translate their findings to be meaningful to policy-makers. Box 1. Characteristics of knowledge brokering * Organizing and managing joint forums for policy-makers and researchers * Building relationships of trust * Setting agendas and common goals * Signalling mutual opportunities * Clarifying information needs * Commissioning syntheses of research of high policy relevance * Packaging research syntheses and facilitating access to evidence * Strengthening capacity for knowledge translation * Communicating and sharing advice * Monitoring impact on the know--do gap Although a few successful case studies using knowledge brokering have been reported, (5,6) important questions remain unanswered. * How can the tension between scientific rigour and timely relevance to policy-making be handled? * The use of evidence from research in policy-making often implies the need to interpret the specific significance of the research findings for the policy decision in question. Who should be involved in each part of this translation? * Who should organize the knowledge brokering process and how can it be institutionalized? We describe two experiences with the knowledge brokering approach and provide an outlook for next steps. Informing policy on subfertility care in the Netherlands The Netherlands' Minister of Health in October 2003 decided to no longer reimburse the first cycle of in-vitro fertilization (IVF) and all medications for fertility treatments, except those for the second and third IVF cycles. The decision was not based on cost-effectiveness evidence. Because the results from cost-effectiveness studies were about to become available, the Netherlands Organisation for Health Research and Development (ZonMw) suggested that clinical researchers conducting six interrelated studies on the cost-effectiveness of subfertility might like to collaborate on how to present their results to facilitate the process of translating evidence and putting it in terms relevant to policymakers. A steering committee was established to get inputs and provide quality control. …

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.