Architecting the Future of Care: A Unified AI and Predictive Analytics Framework for Scalable, Data-Driven Patient Management

Abstract

Contemporary healthcare is rife with increasingly untenable challenges: disconnected data, reactive modes of care delivery, rising costs, and variable outcomes. This paper presents a proposed unified architecture to design for the future of patient management through the integrated use of artificial intelligence (AI) and predictive analytics. The proposed architecture provides a way to represent data-driven, scalable, and proactive healthcare alternatives. The proposed architecture creates an organizational architecture to bring together disparate data inputs (electronic health records [EHRs], wearables, genomics, social determinants of health), enabling predictive modelling at the population and patient level to empower a proactive approach to risk (e.g., disease onset, readmission, health decline) identification, intervention planning, and personalized patient-centered care. The architecture builds upon three key technological enablers: (1) adaptive machine learning algorithms for identifying patterns and associations across multiple data sets; (2) a real-time, predictive analytics engine capable of producing continuous insights for patient health; and (3) standardized and interoperable modules to support flexibility across care settings. Further, the architecture embeds direct clinical decision support within provider workflows to provide actionable intelligence. We outline the value and design features for the framework, as well as key consideration for implementation and action (e.g., data governance, interoperability, and ethical use of artificial intelligence) and the potential to reimagine the way care is delivered. This unified framework for AI and predictive analytics can enable proactive, personally delivered care pathways, allow for optimization of resources and care delivery, and increase overall population health outcomes, and is a solid foundation to built scalable, effective, and data-informed healthcare systems of value for the future.