Moving from

Structured processes to improve the quality and impact of clinical and translational research are a required element of the Clinical and Translational Sciences Awards (CTSA) program and are central to awardees' strategic management efforts. Quality improvement is often assumed to be an ordinary consequence of evaluation programs, in which standardized metrics are tabulated and reported externally. Yet evaluation programs may not actually be very effective at driving quality improvement: required metrics may lack direct relevance; they lack incentive to improve on areas of relative strength; and the validity of inter-site comparability may be limited. In this article, we describe how we convened leaders at our CTSA hub in an iterative planning process to improve the quality of our CTSA program by intentionally focusing on how data collection activities can primarily advance continuous quality improvement (CQI) rather than strictly serve as evaluative tools. We describe our CQI process, which consists of three key components: (1) Logic models outlining goals and associated mechanisms; (2) relevant metrics to evaluate performance improvement opportunities; and (3) an interconnected and collaborative CQI framework that defines actions and timelines to enhance performance.