PRIMARY-AI

Establishing International Consensus on Outcomes-Based Evaluation Framework for Artificial Intelligence in Primary Care

Evaluation for AI in primary care should...

Safety
Fairness
Effectiveness
Generalizability
Usability
Accessibility
People-Centredness
Coordination
Continuity

About

PRIMARY-AI: Patient-centered Research Initiative for Metrics And Responsible Yield in AI. Established in 2025, it is a partnership between over 100 academic, regulatory, policy, industry, and charitable organisations worldwide.

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Evaluation Framework Components

PRIMARY-AI will deliver a comprehensive evaluation framework comprising:

Core Outcome Sets

Validated core outcome sets for major AI application categories for primary care (e.g., diagnostic decision support, clinical documentation, patient triage, data governance, clinical coding standards), specifying what should be measured to demonstrate benefit.

Measurement Instruments

Standardised measurement instruments for assessing AI impact on continuity, coordination, people-centredness, bias, effectiveness and accessibility

Evaluation Standards

Minimum evaluation standards defining evidence thresholds required before AI deployment in primary care.

Implementation Guidance

Implementation guidance stratified by resource setting to ensure applicability from high-income to low-resource contexts.

Resources

Explore our collection of publications, tools, and media related to primary care AI

Publications

Research papers and articles on primary care AI

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Tools

Evaluation tools and frameworks for AI assessment

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Media

Latest news and updates from our team

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Contact

Let's keep in touch!

Interested in our work? For more information or to get involved in our projects, please contact us via the following:

  • Mail: primary-ai@tsinghua.edu.cn