Translating evidence into practice: what’s your paradigm map?

Leading up to Evidence Live 2016, we will be publishing a series of blog posts highlighting projects, initiatives and innovative ideas from future leaders in evidence based medicine.
Please read on for the second in the series from Kristin Danko at the University of Ottawa.
If you are interested in submitting a blog post, please contact alice.rollinson@phc.ox.ac.uk. Stay tuned! 

“[Paradigms function] by telling the scientist about the entities that nature does and does not contain and about the ways in which those entities behave. That information provides a map whose details are elucidated by mature scientific research. And since nature is too complex and varied to be explore at random, that map is as essential as observation and experiment to science’s continuing development” – T. Kuhn, pg. 109 (1)

Translating evidence into practice, and in turn developing the science of translation is complex, challenging work. Several interrelated disciplines have arisen to address this challenge (e.g., implementation science, knowledge translation, quality improvement, among others) to determine the methods that most effectively get evidence into practice to improve health services and care. While the global objective of these disciplines is essentially the same, their methods, terminology and underlying epistemological frameworks are diverse (although not wholly indistinguishable) (2). Nilsen for example, identified over 40 theories, models and frameworks guiding the design, evaluation and interpretation of implementation studies (3). Lokker and colleagues noted 51 diverse classification schemes for characterizing the content of implementation interventions (4).

With so many options to choose from, is it any wonder that syntheses of implementation studies observe such diverse permutations of interventions with correspondingly high variation of effect (to say nothing of studies produced by researchers still choosing to remain agnostic to theories, models, and shared terminologies…). While such diversity of approaches speaks to the multidimensional nature of the phenomena being studied, it may limit the efficiency and effectiveness with which we are able to develop a cumulative science and may contribute to research waste (5).

How then, as a scientific community do we push this field forward to actualize the benefits of translating knowledge into practice and improve patient care? How do we become more scientific?

In considering such normative questions, I considered implementation science (broadly defined) through the lens of Thomas Kuhn’s classic, The Structure of Revolutions (1).  If a paradigm is the map guiding research –that is, the force defining the realm of acceptable questions, methods, terminologies and solutions – then implementation science is currently operating under the direction of multiple competing and overlapping paradigms. Indeed, Kuhn’s articulation of a period of ‘extraordinary research’ (“The proliferation of competing articulations, the willingness to try anything, the expression of explicit discontent, the recourse to philosophy and to debate over fundamentals”, Kuhn, pg. 91 (1)) seems particularly apt in describing the current state of implementation science. Yet extraordinary research does not produce cumulative knowledge. Rather, one paradigm (or perhaps several complementing, but not incompatible paradigms) must emerge in order for productive science to be executed and global understanding advanced.

If this thought exercise is true, then what next? While it is difficult to know how to best achieve a more efficient and effective scientific state, researchers interested in translating evidence into practice could consider the following in their future studies with respect to implementation science paradigms:

1. Become aware of the plethora of existing paradigms and their elements; build studies to empirically evaluate and extend existing paradigm elements (e.g., compare the effectiveness of two implementation models) instead of creating new ones.
2. Transparently report the choice of paradigm(s) over others, and comprehensively report paradigm elements using pre-existing terminologies and guidelines.
3. Engage in cross-paradigm collaboratives to promote shared agreement of terminologies and methods, and systematic and synergistic evaluation of interventions.

Perhaps with these objectives in mind, we may shape future paradigms to better support our scientific understandings, rather then obfuscate them.

Kristin Danko is a second year doctoral student in the Department of Epidemiology at the University of Ottawa, and a research coordinator the Ottawa Hospital Research Institute.  She is interested in improving synthesis methods for implementation science/knowledge translation interventions as well as knowledge translation methods for improving the conduct of primary studies themselves.

1. Kuhn TS. The Structure of Scientific Revolutions. 4th editio. London: The University of Chicago Press; 1962.
2. Walshe K. Pseudoinnovation: the development and spread of healthcare quality improvement methodologies. Int J Qual Health Care [Internet]. 2009 Jun [cited 2016 Feb 26];21(3):153–9. Available from: http://www.ncbi.nlm.nih.gov/pubmed/19383716
3. Nilsen P. Making sense of implementation theories, models and frameworks. Implement Sci [Internet]. BioMed Central; 2015 Jan 21 [cited 2016 Jan 3];10(1):53. Available from: http://implementationscience.biomedcentral.com/articles/10.1186/s13012-015-0242-0
4. Lokker C, McKibbon KA, Colquhoun H, Hempel S. A scoping review of classification schemes of interventions to promote and integrate evidence into practice in healthcare. Implement Sci [Internet]. 2015 Dec [cited 2015 Mar 26];10(1):220. Available from: http://www.implementationscience.com/content/10/1/27
5. Ivers NM, Grimshaw JM, Jamtvedt G, Flottorp S, O’Brien MA, French SD, et al. Growing literature, stagnant science? Systematic review, meta-regression and cumulative analysis of audit and feedback interventions in health care. J Gen Intern Med [Internet]. Springer; 2014 Nov 1 [cited 2015 Jan 3];29(11):1534–41. Available from: /pmc/articles/PMC4238192/?report=abstract