New Commentary Explores the Power of Data-Driven Implementation Trials to Advance Learning Health Systems

October 30, 2025

A new commentary, “Data-Driven Implementation Trials: Realizing Their Full Potential in Achieving the Promise of Learning Health Systems,” has been published in Learning Health Systems. The paper, authored by Charis X. Xie, PhD (Wolfson Institute of Population Health, Queen Mary University of London), Patricia D. Franklin, MD, MBA, MPH (Department of Medical Social Sciences, Feinberg School of Medicine, Northwestern University), Theresa L. Walunas, PhD, (Department of Medical Social Sciences and Department of General Internal Medicine, Feinberg School of Medicine, Northwestern University), and Rinad S. Beidas, PhD (Department of Medical Social Sciences, Feinberg School of Medicine, Northwestern University) examines how data-driven implementation trials can transform the way healthcare systems learn, adapt, and improve.

As healthcare becomes increasingly data-rich, health systems are positioned to use real-time analytics to drive quality improvement (QI). The authors offer that implementation science (IS) provides complementary frameworks and tools needed to existing QI approaches by systematically assessing context and defining sustainable and scalable strategies that can be generalized across contexts.

The commentary positions data-driven implementation trials as essential tools within learning health systems (LHS). By embedding randomized implementation studies into routine care and leveraging existing clinical data, these trials enable rigorous comparisons of different implementation strategies —revealing which approaches most effectively improve adoption, fidelity, and sustainment of evidence-based practices under real-world conditions. This approach not only refines healthcare delivery in real time but also accelerates the cycle of learning that underpins LHS, alongside existing health system approaches.

Drawing on lessons from large health systems in the United Kingdom and the United States, the authors present actionable recommendations to realize the potential of data-driven implementation trials. They call for:

Strengthening health system infrastructure to support data integration and analysis
Building collaborative partnerships between researchers, clinicians, and operational leaders
Securing long-term institutional commitment and funding
Cultivating a culture grounded in implementation science to enhance and expand QI efforts

Ultimately, the authors conclude that data-driven implementation trials serve as catalysts for scalable, equitable, and sustainable healthcare innovation. While widespread adoption remains a work in progress - even in well-resourced systems - the framework they propose offers a clear roadmap for realizing the promise of learning health systems worldwide.

Beidas noted, “It was a gift to have Dr. Xie join us for a few months last fall as a visiting scholar from Queen Mary University of London - and this paper represents the collaborative thinking that we had the opportunity to do together. I appreciate Dr. Xie’s leadership!” Xie reflected, “It was a wonderful experience to conduct a research visit at Northwestern University, where I had the opportunity to learn from the department’s rich transdisciplinary perspectives and to integrate knowledge across cultures between the US and UK.”