MAPPING AND NAVIGATING THE HEALTH AI ECOSYSTEM
Discussion Points ▪ The AI Forum is a non-profit organisation founded in 2017 to connect AI innovators, end users, investors, regulators, researchers, educators and entrepreneurs ▪ The Health AI Working Group was established following the AI Forum's blueprint for AI in Aotearoa, which identified healthcare as a key sector for AI transformation ▪ Participants discussed barriers to AI adoption in healthcare including regulatory uncertainty, lack of clear governance frameworks, and challenges with data access ▪ Radiology was highlighted as a sector with established AI implementation that could provide learnings for other healthcare areas ▪ Concerns were raised about the sale of MedTech (used by 85% of GPs) to a Canadian company and implications for patient data ▪ Discussion of the need for risk-proportionate approaches to AI regulation, with different standards for clinical decision support versus productivity tools ▪ Participants noted the gap in medical device regulation in New Zealand, with no pre-market authorisation or post-market surveillance requirements Key Actions ▪ Attendees encouraged to sign up to the AI Forum register to build connections across the health AI ecosystem ▪ Proposal to develop interim guidance for healthcare-specific AI implementation while waiting for formal regulation ▪ Suggestion to create a framework for quality checks of AI tools (e.g., quarterly reviews of clinical scribes) ▪ Recommendation to establish a mechanism for sharing experiences with specific AI products and vendors ▪ Proposal to develop shared training resources for AI literacy across healthcare organisations ▪ Suggestion to create a classification framework that helps identify risk levels for different AI use cases Additional Notes ▪ Current regulatory timeline suggests medical products bill won't be in place until 2028 ▪ Distinction made between software as medical device (requiring higher regulation) versus productivity tools ▪ Participants discussed the challenge of balancing innovation with appropriate guardrails ▪ Concerns raised about automation bias, where clinicians may stop checking AI outputs after becoming comfortable with tools ▪ Discussion of data sovereignty issues and challenges with New Zealand's limited computing infrastructure ▪ Participants noted the need for better education about different types of AI and their appropriate applications
Table sponsored by
- 20 -
Powered by FlippingBook