Transforming an Autism Pediatric Research Network into a Learning Health System: Lessons Learned. Issue 2 (March 2019)

• Record Type: Journal Article
• Authors: Murray, Donna S.; S. Anixt, Julia; Coury, Daniel L.; Kuhlthau, Karen A.; Seide, Janet; Kelly, Amy; Fedele, Angie; Eskra, Diane; Lannon, Carole
• Is Part Of: Pediatric quality & safety. Volume 4:Issue 2(2019)
• Publication Date: 2019-03
• Subjects: Pediatric nursing -- Periodicals; Pediatrics -- Periodicals; Patients -- Safety measures -- Periodicals; Children -- Hospital care -- Periodicals; 618.92
• DOI: 10.1097/pq9.0000000000000152
• Languages: English
• ISSNs: 2472-0054

Abstract

Abstract : Introduction: The Autism Speaks Autism Treatment Network that serves as the Autism Intervention and Research Network on Physical Health (ATN/AIR-P) has a mission to improve the health and well-being of children with Autism Spectrum Disorder and determine the best practices that lead to improved outcomes and expedite the translation of findings to practice. To better achieve this mission, the ATN/AIR-P is engaging in a design process to transition to a Learning Network (LN), the Autism Learning Health Network. The purpose of this paper is to: (1) make the medical and patient communities aware of an Autism LN that is based on the Institute of Medicine's definition of a Learning Health System; (2) describe how and why the ATN/AIR-P transformed to an LN; and (3) share lessons learned that might inform the transition of future existing networks surrounding other conditions. Methods: Design methods included: an in-person design session with various stakeholders, the development of a Key Driver Diagram and redesign of organizational processes, network governance, and data collection and analytics. Results: We realized many benefits in making the transition to an LN along with many lessons that can inform the design and implementation of the LN model when transforming existing networks to learning health systems. Conclusions: Transitioning a well-established research network requires a complex redesign of existing processes, data infrastructure, and cultural shifts compared with developing a new LN. We identified factors that may inform the transition of future established networks to expedite the process.