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Issues And Trends In Healthcare Delivery System01:29

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The issues and trends in healthcare delivery are constantly changing. The COVID-19 pandemic is one recent issue that wreaked havoc on healthcare systems, causing a shortage of healthcare workers, high demand for medicines and supplies, and increased medical expenditure due to a lack of insurance. Other issues include rising healthcare costs and care fragmentation.
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Payment for healthcare services has historically promoted adoption of costly and often unnecessary or inefficient...
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Bridging the Implementation Gap in Medical AI Education: 3-Lever Framework for Concurrent Reform.

Sherrie L Kelly1, Melissa Forgie2, Mark C Walker1,2,3

  • 1Clinical Epidemiology Program, Ottawa Hospital Research Institute, 501 Smyth Road, Ottawa, ON, K1H 8L6, Canada, 1 613-761-4395.

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|April 28, 2026
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Medical schools need to integrate artificial intelligence (AI) training for physicians. A new framework proposes simultaneous updates to faculty development, curriculum, and regulation for effective AI education.

Keywords:
AIaccreditationartificial intelligencecurriculumhealth equitymedical undergraduate education

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Area of Science:

  • Medical Education
  • Artificial Intelligence in Healthcare
  • Health Professions Education

Background:

  • Rapid AI integration in clinical practice requires updated medical education and physician assessment.
  • Current AI education in Canadian medical schools is inconsistent, with minimal formal training for students.
  • Existing national AI principles lack practical guidance for educational and regulatory implementation.

Purpose of the Study:

  • To propose a concurrent implementation framework for integrating AI competencies into medical education.
  • To address the deficit in practical AI education guidance by proposing a new model.
  • To outline actionable steps for deans and regulators to embed AI competence.

Main Methods:

  • Conceptualizing AI curriculum implementation as a problem of concurrent lever activation.
  • Proposing a 3-lever concurrent implementation framework: clinician-educator capacity, digitally enabled learning environments, and regulatory/assessment reform.
  • Extending existing AI competency frameworks with a focus on simultaneous reform.

Main Results:

  • A traditional, sequential reform model is inadequate for AI's rapid evolution and risks.
  • The proposed 3-lever framework ensures AI competencies transition from abstract to practical application.
  • Simultaneous and aligned activation of faculty development, curriculum, and regulation is crucial.

Conclusions:

  • A concurrent implementation framework is essential for effectively integrating AI into medical education.
  • This model provides a transferable blueprint for embedding AI competence in competency-based medical education systems.
  • Minimum concurrent actions are outlined for effective AI education reform in healthcare.