The goal of medical education is to produce a physician workforce capable of delivering high-quality equitable care to diverse patient populations and communities. To achieve this aim amidst explosive growth in medical knowledge and increasingly complex medical care, a system of personalized and continuous learning, assessment, and feedback for trainees and practicing physicians is urgently needed. In this perspective, the authors build on prior work to advance a conceptual framework for such a system: precision education (PE).PE is a system that uses data and technology to transform lifelong learning by improving personalization, efficiency, and agency at the individual, program, and organization levels. PE "cycles" start with data inputs proactively gathered from new and existing sources, including assessments, educational activities, electronic medical records, patient care outcomes, and clinical practice patterns. Through technology-enabled analytics , insights are generated to drive precision interventions . At the individual level, such interventions include personalized just-in-time educational programming. Coaching is essential to provide feedback and increase learner participation and personalization. Outcomes are measured using assessment and evaluation of interventions at the individual, program, and organizational levels, with ongoing adjustment for repeated cycles of improvement. PE is rooted in patient, health system, and population data; promotes value-based care and health equity; and generates an adaptive learning culture.The authors suggest fundamental principles for PE, including promoting equity in structures and processes, learner agency, and integration with workflow (harmonization). Finally, the authors explore the immediate need to develop consensus-driven standards: rules of engagement between people, products, and entities that interact in these systems to ensure interoperability, data sharing, replicability, and scale of PE innovations.
Desai D, Goss G, Al-Hassani A, Gurnani B, Buckley JD, Ismail L, et al. Precision education: the future of lifelong learning. Medical Teacher. 2023;45(7):689–92. doi:10.1080/0142159X.2023.2220175.
García Dieguez M. Comment on the Precision Education in Health: The Future of Personalized and Lifelong Learning?. [Internet]. Pan American Health Organization. Bibliographic Repository. Cited on 07/10/2025. Available at: https://campus.paho.org/en/repo/precision-education-health-future-personalized-and-lifelong-learning
García Dieguez M.
CEEProS Universidad Nacional del Sur
This thought-provoking article invites readers to rethink traditional models of continuing medical education and lifelong learning. It introduces the concept of “precision education” as an emerging approach inspired by precision medicine, which promotes highly personalized learning experiences tailored to the cognitive, emotional, and contextual characteristics of the individual. This reading is especially relevant for educational leaders, continuing education coordinators, and academics interested in the future of post-pandemic medical education and the recognition of diverse professional pathways.
The article argues that medical education must evolve toward models where data on performance, learning styles, engagement levels, and emotional outcomes are used to adapt educational trajectories. It acknowledges that current approaches tend to be uniform, limiting their actual formative impact.
Highlighted elements include the use of technologies such as artificial intelligence, advanced learning management systems (LMS), and predictive models that anticipate student needs. The text also underscores the importance of integrating well-being, motivation, and sociocultural context into educational decision-making.
Although conceptual rather than empirical, and lacking a concrete methodological proposal or research results, its strength lies in opening a critical reflection on the limitations of traditional systems and the need for data-informed educational transformation. The article notes that precision education still requires clearer definition and practical application, but it opens the door to new research and critical analysis of current practices.
- Encourages a critical review of standardized continuing medical education models.
- Suggests designing adaptive learning environments tailored to individual professional profiles.
- Promotes the use of technology for personalized learning pathways.
- Recommends integrating emotional and motivational dimensions into educational decision-making.
- Reinforces the need to use longitudinal data in personalized curriculum design.
- Offers an innovative conceptual framework for future research on individualized learning in health professions.