USA Law and Practice Contributed by: Nadia de la Houssaye, Andy Lee, Jason Loring and Graham Ryan, Jones Walker LLP
errors and omissions coverage, and AI-specific pro - fessional liability policies. Insurance carriers increas - ingly evaluate AI-related risks during underwriting processes, requiring detailed information about AI system deployment, governance frameworks and risk management practices. Organisations with robust AI governance may qualify for preferred pricing or cover - age terms. 10.4 Best Practices for Implementation Organisations considering the implementation of healthcare AI should: • conduct an organisational readiness assessment – such assessments evaluate technical infrastruc - ture, staff capabilities, regulatory compliance frameworks and cultural readiness for AI adoption, identifying gaps and development needs before AI deployment begins; • create multidisciplinary implementation teams – these teams should include clinical leaders, infor - mation technology specialists, legal and compli - ance professionals, and quality assurance experts, and be given clear authority and accountability for AI implementation decisions; • consider phased implementation approaches – such an approach may begin with lower-risk AI applications and gradually expand to more com - plex systems as organisational capabilities and experience develop; • establish training and change management infra - structure – comprehensive training programmes ensure healthcare professionals understand AI system capabilities, limitations and appropriate use while supporting successful adoption and compli - ance;
• emphasise quality assurance – ongoing QA pro - grammes monitor AI system performance and implementation effectiveness while identifying opportunities for improvement and optimisation; • prioritise patient communication and engagement – healthcare organisations should develop clear policies and procedures for communicating with patients about AI system use, including disclosure requirements and consent processes; and • implement AI governance – healthcare organisa - tions should implement AI governance practices, including the implementation of risk assessment frameworks aligned with National Institute of Standards and Technology (NIST) guidelines, con - tinuous monitoring programmes tracking algorithm performance and bias metrics, procedures for AI-related incidents and regulator assessments and audits of AI systems. 10.5 Cross-Border Considerations To navigate cross-border deployment of healthcare AI, organisations should pay specific attention to the following, among other issues: • regulatory harmonisation; • data transfer and privacy requirements; • professional licensing and practice standards;
• intellectual property protection; • compliance co-ordination; and • risk management strategies.
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