AI SCRIBES ARE HERE – WHAT TOOLS ARE NEXT FOR PRIMARY CARE?
Discussion Points ▪ AI scribes are already widely adopted in primary care; discussion focused on what tools should come next ▪ Data quality is essential for effective AI implementation; poor coding in general practice is a significant barrier ▪ Clinical decision support tools could benefit urgent care systems and rural practices with limited resources ▪ AI agents could improve triage and appointment booking, directing patients to the most appropriate care provider ▪ Potential for AI to analyse patient populations and help identify optimal workforce composition for community needs ▪ Opportunity for AI to streamline administrative processes like ACC claiming and inbox management ▪ Need for frameworks that help practices assess and implement AI tools with appropriate safeguards Key Actions ▪ Develop a simplified framework for practices to evaluate AI tools (current framework is 50 pages and too complex) ▪ Explore integration of AI tools with patient portals to provide NZ-specific health information ▪ Investigate "matching service" concept to connect patients with appropriate community providers ▪ Consider how AI can help identify missed revenue opportunities in practices (e.g., unclaimed ACC) ▪ Engage with vendors to develop AI-to-AI communication capabilities between systems Privacy concerns remain the biggest barrier to AI adoption in practices ▪ Tension exists between maintaining human connection in healthcare while leveraging AI efficiencies ▪ Different demographic groups have different preferences for digital vs human interaction ▪ Cost is a significant barrier for some AI tools (e.g., triage bots can cost $1-10 NZD per triage) ▪ Need to balance risk management with innovation when implementing new AI tools ▪ Māori data sovereignty and disability inclusion must be considered in AI tool development Additional Notes ▪
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