Learning from Data for Improvement

3 credits · Graduate

This course explores the “what,” “why,” and “how” of measurement to support learning and improvement. Through a blend of synchronous and asynchronous online learning, case studies, and group discussions, learners will examine the critical role of measurement in improvement science, how it differs from measurement for research or accountability. Participants will be introduced to measurement frameworks, including foundational models such as Donabedian’s Triad and contemporary approaches for developing dashboards and optimizing data visualization. Using the lens of complexity, learners will consider how to design internal quality monitoring strategies and apply measurement tools effectively within improvement efforts. The course emphasizes the importance of understanding variation, introducing statistical methods tailored to identifying, interpreting, and managing variation in the context of improvement. A strong focus will be placed on equity and people-centered measurement strategies that ensure data informs the needs of those closest to the work and the communities they serve.