10P-Health: A Conceptual Framework for Continuous, Digitally Enabled Precision Health and Wellness

Abstract

Personalized medicine has advanced individualized prevention, diagnosis, and treatment through genomics, multi-omics, and artificial intelligence. Nevertheless, its implementation remains constrained by fragmented data, limited interoperability, episodic care, privacy concerns, and the insufficient use of behavioral, environmental, social, and continuously generated health information. Building on the evolution from P4 to later “P” models, this position paper proposes 10P-Health as a broader conceptual framework for holistic, continuous, individual-centered, and digitally enabled health and wellness.

The framework integrates ten core principles: Predictive, Preventive, Personalized/Precision, Proactive, Participatory, Pertinent, Pervasive, Permanent, Privacy-Preserving, and Platform-Based. Together, these principles connect individualized risk assessment and intervention with individual participation, longitudinal monitoring, contextual relevance, responsible data use, and interoperable digital infrastructure. To translate the concept into practice, the paper presents a layered reference architecture linking multimodal data acquisition, harmonization, secure integration, analytics, decision support, individual engagement, and controlled secondary research.

Real-world adoption requires balancing the framework’s principles while addressing technological, operational, ethical, and legal challenges, including data generation and usage, data quality, clinical validation, workflow redesign, professional accountability, consent, equity, reimbursement, and sustainable governance. The paper recommends implementing 10P-Health through defined use cases, stakeholder-led pilots, continuous evaluation, and progressive scaling. It offers a structured direction for transforming advances in digital health and multimodal data into responsible, continuous, and sustainable personalized health and care.