Creating, Sustaining, and Evaluating Personalized Digital Health Systems

Personal health informatics (PHI) aims to provide individuals with personalized, actionable health insights through digital platforms. Despite advancements in digital health, a standardized framework to evaluate the personalization of digital health solutions remains absent. Developers often rely on "free-form" or "weak" personalization, contributing to high user attrition and non-personalized "cold start" experiences. This paper examines the evolution of personalization in digital health, covering early web-based systems, data-driven advancements, behavioral theory integration, and AI-driven personalization. We propose the development of PERSEID (Personalization Index for Digital Health) to measure and enhance personalization in digital health. This index, guided by a comprehensive ontology, will assess multiple personalization dimensions, adapting to users' evolving behaviors over time. By addressing current gaps and establishing a validated personalization framework, PERSEID aims to enhance the effectiveness of personalized digital health systems, ultimately advancing the field of PHI and supporting improved health outcomes.