AI Article Synopsis

  • Health policymakers are prioritizing diabetes prevention but lack clear strategies for effective interventions; the Diabetes Population Risk Tool (DPoRT) has been created to predict diabetes risk using population data.
  • The study aims to enhance the use and effectiveness of DPoRT through partnerships, training, and understanding barriers, in order to support public health decision-makers in Ontario and Manitoba.
  • A mixed-methods evaluation approach will analyze the outcomes of these efforts, utilizing both quantitative and qualitative data from various health organizations.

Article Abstract

Background: Health policy makers have stated that diabetes prevention is a priority; however, the type, intensity, and target of interventions or policy changes that will achieve the greatest impact remains uncertain. In response to this uncertainty, the Diabetes Population Risk Tool (DPoRT) was developed and validated to estimate future diabetes risk based on routinely collected population data. To facilitate use of DPoRT, we partnered with regional and provincial health-related decision makers in Ontario and Manitoba, Canada. Primary objectives include: i) evaluate the effectiveness of partnerships between the research team and DPoRT users; ii) explore strategies that facilitate uptake and overcome barriers to DPoRT use; and iii) implement and evaluate the knowledge translation approach.

Methods: This protocol reflects an integrated knowledge translation (IKT) approach and corresponds to the action phase of the Knowledge-to-Action (KtoA) framework. Our IKT approach includes: employing a knowledge brokering team to facilitate relationships with DPoRT users (objective 1); tailored training for DPoRT users; assessment of barriers and facilitators to DPoRT use; and customized dissemination strategies to present DPoRT outputs to decision maker audiences (objective 2). Finally, a utilization-focused evaluation will assess the effectiveness and impact of the proposed KtoA process for DPoRT application (objective 3). This research design utilizes a multiple case study approach. Units of analyses consist of two public health units, one provincial health organization, and one provincial knowledge dissemination team whereby we will connect with multiple regional health authorities. Evaluation will be based on analysis of both quantitative and qualitative data collected from passive (e.g., observer notes) and active (e.g., surveys and interviews) methods.

Discussion: DPoRT offers an innovative way to make routinely collected population health data practical and meaningful for diabetes prevention planning and decision making. Importantly, we will evaluate the utility of the KtoA cycle for a novel purpose - the application of a tool. Additionally, we will evaluate this approach in multiple diverse settings, thus considering contextual factors. This research will offer insights into how knowledge translation strategies can support the use of population-based risk assessment tools to promote informed decision making in health-related settings.

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Source
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC3998044PMC
http://dx.doi.org/10.1186/1748-5908-9-35DOI Listing

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Article Synopsis
  • Health policymakers are prioritizing diabetes prevention but lack clear strategies for effective interventions; the Diabetes Population Risk Tool (DPoRT) has been created to predict diabetes risk using population data.
  • The study aims to enhance the use and effectiveness of DPoRT through partnerships, training, and understanding barriers, in order to support public health decision-makers in Ontario and Manitoba.
  • A mixed-methods evaluation approach will analyze the outcomes of these efforts, utilizing both quantitative and qualitative data from various health organizations.
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