Translational research applies basic science discoveries in clinical and community settings. Implementation research is often limited by tremendous variability among settings; therefore, generalization of findings may be limited. Adoption of a novel procedure in a community practice is usually a local decision guided by setting-specific knowledge. The conventional statistical framework that aims to produce generalizable knowledge is inappropriate for local quality improvement investigations. We propose an analytic framework based on cost-effectiveness of the implementation study design, taking into account prior knowledge from local experts. When prior knowledge does not indicate a clear preference between the new and standard procedures, local investigation should guide the choice. The proposed approach requires substantially smaller sample sizes than the conventional approach. Sample size formulae and general guidance are provided.