August  2011

We launched this blog online last month with a promise to report on the results of a workshop I chaired in Montreal on the challenges of translating data into policy. I will not repeat here what has been reported in an article about the workshops in the July/August issue the Epi Monitor. Instead I will make good on my promise to comment on three questions that I asked our panelists.

What conceptual framework works best to help epidemiologists understand and navigate the process of data translation, what works to successfully translate, and what promising approaches there are.

Frameworks

I did not hear anyone present an overview of different frameworks, but Olivia Carter-Pokras told attendees at her symposium that there are different policy frameworks, none are superior, and all have utility. She stated that the best approach is one based on the context of the policy situation rather than the framework used.

While I do not disagree about the importance of context, I do believe that how an epidemiologist conceptualizes the process he or she is involved in can make a big difference in the actions taken and the results achieved. Along those lines, I heard presenters discuss frameworks that focus on encouraging epidemiologists to “do well what epidemiologists do” as the best way to translate data into action. Another framework calls for greater understanding and knowledge about the populations for which interventions are desired. Perhaps the most notable framework discussed is the one which envisages data translation as a process epidemiologists cannot conduct alone. It calls for more skill in interacting with non-researchers such as the public and decision makers. Several presenters shared their experience to establish the validity of this conclusion.

Buy-In

A corollary of the collaborative approach is the advisability of involving other players early on in the process from initial problem formulation all the way through to problem resolution. Such participation helps generate better ideas AND more buy-in for the difficult task of policy formulation and implementation. One of the most promising approaches described along these lines was joint fact finding in which stakeholders work together to frame the question, generate data, and analyze and interpret the results.

Slow-Learning

These findings and approaches calling for greater public participation in research are not new. I recall reading a similar lesson from a Hopkins symposium years ago. Yet epidemiologists do not appear to have absorbed this lesson. We are applied scientists with uncertain knowledge about the science of applying what we know. It reminds me of Jonathan Samet’s call years ago for a push to create an epidemiology of translation. I do not think anything ever came of it. Why not?  

I welcome your comments here on all of these topics as we continue to explore epidemiology and policy on this blog.