Many models and frameworks exist depicting the process of research evidence informing practice and policy decisions. My favourite model, however, is simply called Evidence-Informed Decision-Making in Public Health, or EIDM for short. You may have seen this model previously when visiting the website of the National Collaborating Centre for Methods and Tools. This model, which is depicted as five overlapping ovals, is my favorite because it illustrates not only that many different kinds of evidence are used to inform public health decisions, but also just how complex public health decision-making is.
The four overlapping ovals in the background of the model represent unique sources of evidence including research evidence, community health issues and the local context, community and political preferences, and public health resources. The oval in the foreground represents the public health expertise that is needed to integrate all of the relevant evidence from each of the four sources during the decision-making process. The model shows all of the ovals to be equal in size, suggesting each type of evidence exerts an equal amount of influence on the decision, but this is not always the case.
The EIDM model is flexible and allows for differences in the importance of the various sources of evidence across settings and circumstances. The inclusion of evidence related to community health issues and local context, as well as community and political preferences, recognizes that practice and policy decisions will likely vary across public health organizations or geographic locations, even when the same research evidence and similar public health resources are available. For example, a practice or policy decision made for a densely populated city may not be the same as one made for a sparsely populated remote area, even though both jurisdictions considered all four sources of evidence.
However, both decisions would have followed an evidence-informed process. Let's explore this model more closely using a hypothetical public health example. Suppose a report released by a national organization in Canada identified significant variation across the country in rates of respiratory symptoms such as wheezing and shortness of breath among adults aged 18 to 65. Furthermore, the report also found a significant variation in the use of public transportation and that in regions in which public transit usage was higher, respiratory symptoms were lower.
The report concluded by suggesting there was a potential link between use of public transit and respiratory symptoms and suggested health organizations should explore whether changes to the built environment could be a good way to address the challenges of public transit. were needed to address respiratory symptoms. You recall the EIDM model and get to work identifying relevant evidence.
You start by searching for relevant research evidence on the possible link between car emissions and respiratory symptoms, as well as the effectiveness of strategies to alter the built environment to increase the use of public transit. You assess how well the research was conducted and use the best available evidence to draw conclusions about the connection and find effective strategies. You then move on to collecting evidence related to community health issues and the community context. You find that the use of public transit is indeed low in your community. However, you see that car emissions and rates of respiratory symptoms in your community are also lower than the provincial average.
In assessing community and political preferences, you find that most residents in your community travel to other jurisdictions for work. You also learn that residents are worried about noise levels that could result from public transit. Local politicians are reluctant to increase property taxes to pay for public transit and are unsure whether neighbouring jurisdictions will contribute.
Finally, you assess the resources required to develop and implement strategies to alter the built environment and determine that the costs would be substantial. Having collected evidence from all sources identified in the EIDM model, You now rely on your public health expertise to help you make sense of it all. You come to the following conclusions. You have considered the evidence from all sources and found that respiratory symptoms and car emissions in your community are lower than the provincial average, and that the challenges in developing a public transit system that crosses municipal boundaries are significant.
So you weight the community health issues and the community and political preferences more heavily than research and resources. You determine that the best course of action with respect to the built environment is to recommend no changes to your community's public transit strategy at this time. The flexibility of the EIDM model allows decisions to adapt to the distinct qualities of various settings.
Set in another region, your decision regarding the built environment may be influenced by different circumstances. For example, you find in your community high rates of respiratory symptoms and vehicle emissions, and low public transit use, although public transit is available. Among politicians, there is support for increased availability and use of public transit, and interest in exploring funding options. Costs to modify the built environment for public transit are considered high, but attainable.
Remember, the research has established the link between vehicle emissions and respiratory symptoms, as well as effective strategies to promote public transit use. In this example, after considering evidence from all sources, you recommend implementing strategies to encourage the use of public transit. In this case, all sources of evidence contributed significantly to the overall decision.
The two examples provided here illustrate the use of each source of evidence within the EIDM model to make a decision concerning the built environment. Although the research evidence was consistent, the sources of evidence were weighted differently and the decisions reached were different. However, both decisions were evidence-informed.
These examples illustrate how complex public health decision-making can be, and how the influence of different sources of evidence will vary, depending not only on the decision being made, but also the specific circumstances of the setting. This EIDM model is a helpful guide for ensuring all relevant evidence is collected, assessed, synthesized, and prioritized, so that the most appropriate decisions are made for particular settings and circumstances. With a little practice, this model will become second nature in your public health decision making.