Establishing a Cystic Fibrosis Learning Network: Interventions to promote collaboration and data-driven improvement at scale

Introduction

A learning health network is a type of learning health system in which stakeholders use network organization to improve health and health care. Building on existing resources in the cystic fibrosis (CF) community, the Cystic Fibrosis Learning Network (CFLN) was designed to improve medical outcomes and quality of life through an intentional focus on achieving reliable evidence-based chronic care delivery and creating a system for data-driven collaborative learning.

Methods

We describe the development and growth of the CFLN considering six domains of a Network Maturity Grid: system leadership; governance and policy management; quality improvement (QI); engagement and community building; data and analytics; and research. We illustrate the impact of the CFLN experience on chronic care processes and indicators of collaborative infrastructure.

Results

The CFLN represents 36 accredited care centers in the CF Foundation Care Center Network caring for over 6300 patients. Of 6779 patient clinical care visits/quarter, 77% are entered into the CF Foundation Patient Registry within 30 days, providing timely means to track outcomes. Collaborative visit planning is occurring in 93% of clinical care visits to share agenda setting with patients and families. Almost all CFLN teams (94%, n = 34) have a patient/family partner (PFP), and 74% of PFPs indicate they are actively participating, taking ownership of, or leading QI initiatives with the interdisciplinary care team. In 2022, 97% of centers reported completing 1–13 improvement cycles per month, and 82% contributed to monthly QI progress reports to share learning.

Conclusion

The CFLN is a maturing, collaborative infrastructure. CFLN centers practice at an advanced level of coproduction. The CFLN fosters interdisciplinary and PFP leadership and the performance of consistent data-driven improvement cycles. CFLN centers are positioned to respond to rapid changes in evidence-based care and advance the practice of QI and implementation science on a broader scale.