Bridging Translational Gaps in Learning Healthcare Systems

Abstract

Persistent translational gaps continue to limit the impact of scientific discoveries, digital innovations, and evidence-based practices in healthcare, despite major advances in artificial intelligence, data interoperability, and digital health infrastructure. Learning Health Systems (LHS) offer a compelling vision for continuous, data driven improvement, yet most remain aspirational because they lack the sociotechnical mechanisms needed to embed learning into routine practice. Drawing on service science, design science, sociotechnical systems theory, and implementation science, this paper proposes an integrated conceptual framework that combines Translational Service Design (TSD) with LHS principles to address these longstanding barriers. The resulting synthesis clarifies how innovations can move from discovery to implementation to sustained learning, overcoming the “valleys of death” that typically impede adoption. By positioning TSD as the methodological and architectural foundation of LHS, this work offers a coherent pathway for transforming continuous learning from an aspirational ideal into an operational reality, laying the foundation for future empirical validation and technical specification.

Keywords: Learning Health Systems, Translational Service Design, Sociotechnical Systems

DOI: 10.54941/ahfe1007713