Navigating the Landscape of Precision Education: Insights from On-the-Ground Initiatives

A central goal of precision education (PE) is efficiently delivering the right educational intervention to the right learner at the right time. This can be achieved through a PE cycle that involves gathering inputs, using analytics to generate insights, planning and implementing interventions, learning and assessing outcomes, and then using lessons learned to inform modifications to the cycle. In this paper, the authors describe 3 PE initiatives utilizing this cycle. The Graduate Medical Education Laboratory (GEL) uses longitudinal data on graduate trainee behavior, clinical skills, and wellness to improve clinical performance and professional fulfillment. The Transition to Residency Advantage (TRA) program uses learner data from medical school coupled with individualized coaching to improve the transition to residency. The Anesthesia Research Group for Educational Technology (TARGET) is developing an automated tool to deliver individualized education to anesthesia residents based on a longitudinal digital representation of the learner. The authors discuss strengths of the PE cycle and transferrable learnings for future PE innovations. Common challenges are identified, including related to data (e.g., volume, variety, sharing across institutions, using the electronic health record), analytics (e.g., validating augmented intelligence models), and interventions (e.g., scaling up learner assessments with limited resources). PE developers need to share their experiences in order to overcome these challenges, develop best practices, and ensure ethical development of future systems. Adapting a common framework to develop and assess PE initiatives will lead to a clearer understanding of their impact, help to mitigate potential risks, and allow deployment of successful practices on a larger scale.