Background: Substantial gaps often exist between everyday practice and best practice as shown by research. A formal definition of and a measure for quantifying such proof-to-practice gaps could be useful for translating research into practice.

Objectives: To define a framework for analyzing proof-to-practice gaps of both underuse and overuse, and to define an associated measure for quantifying such gaps.

Methods: An intervention's use can be plotted over time as ideal and actual uptake curves among candidates and non-candidates [1]. Gaps of underuse are deviations from ideal uptake among candidates and can be quantified as underuse NNPs (Number Not Prevented): the number of disease events each year that would have been prevented, but were not, because of underuse among candidates of the intervention. Gaps of overuse are deviations from ideal uptake among non-candidates and can be similarly quantified as overuse NNPs.

To illustrate, the underuse gap is the area between an intervention's optimal and actual uptake curves among candidates for potential benefit (Figure 1). Optimally, interventions remain unused until their efficacy has been established (Time A), at which time the proof of efficacy is immediately recognized and all subsequent candidates are treated. In reality, however, interventions are often used before efficacy has been proven (Time A) and appropriate usage increases only after proof of efficacy has been belatedly recognized (Time B). Usage then plateaus at some degree of underuse among candidates.

Results: Applying our method to the underuse of beta_blockers at hospital discharge of post-myocardial infarction (MI) patients in the United States demonstrates an annual NNP of 2995 first-year post-MI deaths not prevented (sensitivity analysis range 455 to 20,409). This compares to an NNP of 2356 deaths not prevented annually due to underuse of influenza vaccination in people over 65 years of age in the United States. The framework can be extended to accommodate multiple target events per intervention (e.g., an annual NNP of 1260 first-year post-MI non-fatal MIs not prevented due to beta-blocker underuse post-MI).

Methodologically, our NNP analysis framework highlights challenges to the determination of efficacy and efficiency, the definition of what constitutes proof, the rapid recognition of proof when it does occur, the definition of eligible candidates, and the definition of the proportion of candidates treated.

Conclusions: The NNP framework provides a systematic approach for describing and analyzing the components of proof-to-practice gaps. The NNP measure factors together the magnitude of an intervention's efficacy, its degree of underuse or overuse, and the population burden of the targeted disease to allow comparisons of the clinical consequences of proof-to-practice gaps across diverse interventions. Despite its current limitations, the NNP framework and measure should help to advance methodological work in translating research into practice, and should be useful for framing efforts to improve evidence-based practice at organizational or population levels.

References: 1. Sim I, Cummings SR. A New Framework for Describing and Quantifying Gaps Between Proof and Practice. Med Care. 2003; 41(8):874-881.