KeyLIME+ [32] Designing Learning That Learns: The Promise of Precision Medical Education
Jan 6, 2026
Sanjay Desai, an internist, intensivist, and chief academic officer known for curriculum innovation and physician well-being, explores precision medical education. He discusses using clinical and ambient data to personalize learning. He describes location-sensing studies, AI reducing documentation time, dashboards that give learners agency, and principles for safe, equitable scaling of these innovations.
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Precision Education Defined And Why It Matters
- Precision education mobilizes data and technology to personalize medical training across the continuum.
- Sanjay Desai frames it as reducing one-size-fits-all friction, improving efficiency, and transferring agency to learners using analytics and AI.
Badge Sensors Revealed Resident Time Archetypes
- Johns Hopkins used badge-based real-time location sensors to collect over 300,000 hours of resident time-motion data.
- They identified bedside vs computer archetypes and found preliminary correlations linking more bedside time with lower burnout.
Passive Clinical Data Solves Assessment Gaps
- Abundant clinical data collected passively can enable reliable competency assessment that human observations alone cannot.
- Continuous no-touch data (location, communication, EMR logs) offers volume and granularity to detect individual variation and learning needs.