Blending quality improvement and research methods for implementation science, Part I: Design and data collection

摘要

The difficulty of translating evidence in the clinical setting lies in our inappropriate expectations for results to mirror findings in the original research. Akin to expecting the gas mileage on a new car to equal that achieved in premarket testing, implementing research findings in a real-world setting will not be equivalent. A great divide exists between the research context (very clean and uninterrupted, often randomized, limited, or with controlled distractions during delivery of the intervention) and the clinical context of everyday life. The rigor of research allows focused interventions, designated "interveners," data collectors, and often additional tools to facilitate the research process. Real-life implementation occurs in myriad contexts, each of which poses opportunities to study the performance of interventions amid the messiness of everyday life. The trick to success lies in thoughtful planning of how one approaches the measurement of messiness.