Dr. Andrew Nguyen, head of Data and AI at Best Buy Healthcare, chats with Alexy about the role of AI in transforming healthcare delivery. Andrew explains how his team is focused on enabling care at home by leveraging AI and machine learning for virtual hospitals and decentralized clinical trials. A key challenge in this space is managing patient data across different health systems, hospitals, and pharmaceutical companies. He introduces the concept of Context Engineering—a systematic approach to integrating business context into data workflows—to address data interpretation, interoperability, and decision-making issues. By making context explicit rather than implicit, healthcare AI models can become more accurate, scalable, and generalizable across different institutions.

The conversation further explores why healthcare data interoperability remains a major challenge, even after decades of technological advancements. Andrew argues that a lack of explicit context in data exchange is a key reason why AI solutions often fail to generalize across different hospitals. He suggests that leveraging graph databases, multimodal AI models, and metadata frameworks can help structure and manage contextual information more effectively. By shifting the paradigm from just data transmission to context-aware data modeling, Best Buy Healthcare and the broader industry can build more robust AI-driven healthcare solutions. This discussion highlights an evolving convergence of AI, data engineering, and healthcare, underscoring the urgency of addressing context to unlock AI’s full potential in medical applications.

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