Designing and Conducting Scholarly Quality Improvement: A Practical Guide for Improvers Everywhere

Successful publication of quality improvement (QI) work is predicated on the use of established QI frameworks and rigorous analytical methods that allow teams to understand the impact of interventions over time. This article is meant to help QI teams disseminate their work more broadly through publication by providing tangible methods that many journals desire in QI articles with specific examples of published works referenced throughout the article. We introduce improvement frameworks that teams should identify early and use as a foundation throughout their projects. We review vital aspects of QI projects, such as team formation, creation of a succinct and clear aim statement, defining primary, process, and balancing measures, as well as QI tools like key driver diagrams, Ishikawa (fishbone) diagrams, and Pareto charts. Finally, we highlight the importance of analyzing data over time to understand the impacts of plan-do-study-act cycles on data. Annotated run charts or, more preferably, annotated statistical process control (or Shewhart) charts are both statistically sound methods to identify significant changes over time. Deliberate planning and execution of QI projects using these concepts will lead to improved chances of QI teams finding success in their project and eventual article acceptance.