Draft a one-page AI use policy for your department based on the framework in this lesson. Share it with one colleague for feedback.
Your Role as an AI-Literate Clinician
You don't need to be a technologist to lead AI adoption in your department. You need to understand what AI can and cannot do, be willing to pilot tools systematically, and create psychological safety for staff to raise concerns.
The best clinical AI adoptions are led by clinicians — not IT, not administration. Clinicians who understand both the clinical workflow and the AI tool's capabilities are irreplaceable in implementation.
What Your Department AI Policy Needs
A practical department AI policy covers: approved tools, prohibited uses, documentation requirements, patient consent, data governance, and how to report errors.
You don't need a 20-page policy. You need clear answers to: What can we use? What can we not do? What do we document? What do we tell patients?
Key Points
- Approved tools: list specific tools with BAAs or institutional approval
- Prohibited uses: direct clinical decision-making without clinician review, non-HIPAA-compliant tools with patient data
- Documentation: when and how AI assistance should be noted in the record
- Reporting: where to report AI errors (safety reporting system, not just informal mention)
Building AI Literacy on Your Team
Staff who are scared of AI will avoid it. Staff who are overconfident in AI will trust it too much. The goal is calibrated confidence — understanding both the capability and the limits.
Start with ambient documentation if available. It has the best onboarding experience, clearest ROI, and lowest risk. Staff see immediate value and build confidence to explore other applications.
The biggest mistake in AI adoption is mandating use without adequate training and support. Identify 2-3 early adopters who are curious and positive, let them pilot, and use their experience to train others.
Measuring Whether AI Is Actually Helping
Don't assume AI is helping. Measure it. Track documentation time before and after. Survey staff on cognitive burden. Monitor note quality. Track patient satisfaction with communication.
Be honest about the results. If an AI tool isn't delivering value in your specific setting, it's okay to stop using it. Not every tool that works somewhere will work everywhere.
Key Points
- Track documentation time per encounter before and after AI adoption
- Survey staff on burnout and cognitive burden at baseline and follow-up
- Review a sample of AI-generated documentation for accuracy at 30, 60, 90 days
- Measure patient satisfaction specifically related to communication and documentation quality
Day 5 Complete
- Have a framework for building department AI policy
- Know how to train staff with calibrated AI confidence
- Can measure whether AI adoption is delivering value
- Positioned to lead responsible AI adoption in your clinical setting
You finished the course.
Well done. Take what you learned and apply it. The bootcamp is for those who want to go further with live instruction.
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