HONE: A learning health system platform for advancing early intervention in first episode psychosis

Abstract

The emergence of psychosis in early adulthood necessitates rapid, specialized care to improve outcomes and reduce the duration of untreated psychosis. Early intervention services (EIS) for First Episode Psychosis (FEP) are exemplars of healthcare reform but face challenges in sustaining durable improvements across patients' lifetime illnesses. Learning Health Systems (LHS) present a transformative framework, integrating care delivery with continuous quality improvement and research. In this paper, we detail the development and evolution of the Health Outcomes Network and Education (HONE), a novel informatics platform designed to support an LHS for FEP.

HONE facilitates data harmonization, analytics, and visualization to drive quality improvement, leveraging user-centered design to engage clinicians and align with clinical workflows. The platform emphasizes evidence-based outcomes, integrating diverse data sources, including patient-reported outcomes, clinical assessments, and external datasets, within a harmonized repository. By employing a minimalist, question-based approach to data visualization, HONE delivers actionable insights that inform clinical practice while generating research questions to improve care.

We discuss key lessons from HONE's development, including the importance of user engagement, iterative refinement, and balancing standardization with site-specific flexibility. HONE has been successfully deployed across multi-site networks, demonstrating its scalability and adaptability to diverse healthcare settings. This paper highlights HONE's contributions to bridging the gap between knowledge and care, fostering bi-directional knowledge translation, and advancing mental health outcomes. Future efforts will focus on expanding HONE's reach, integrating predictive analytics, and evaluating its long-term impact on FEP care within the LHS framework.