Collaborative networks for both improvement and research

Abstract

Moving significant therapeutic discoveries beyond early biomedical translation or T1 science and into practice involves: (1) T2 science, identifying "the right treatment for the right patient in the right way at the right time" (eg, patient-centered outcomes research) and tools to implement this knowledge (eg, guidelines, registries); and (2) T3 studies addressing how to achieve health care delivery change. Collaborative improvement networks can serve as large-scale, health system laboratories to engage clinicians, researchers, patients, and parents in testing approaches to translate research into practice. Improvement networks are of particular importance for pediatric T2 and T3 research, as evidence to establish safety and efficacy of therapeutic interventions in children is often lacking. Networks for improvement and research are also consistent with the Institute of Medicine's Learning Healthcare Systems model in which learning networks provide a system for improving care and outcomes and generate new knowledge in near real-time. Creation of total population registries in collaborative network sites provides large, representative study samples with high-quality data that can be used to generate evidence and to inform clinical decision-making. Networks use collaboration, data, and quality-improvement methods to standardize practice. Therefore, variation in outcomes due to unreliable and unnecessary care delivery is reduced, increasing statistical power, and allowing a consistent baseline from which to test new strategies. In addition, collaborative networks for improvement and research offer the opportunity to not only make improvements but also to study improvements to determine which interventions and combination of strategies work best in what settings.

Keywords: Learning Healthcare System; Learning Networks; Rapid Learning Networks; quality improvement.