Prescribes requirements and safeguards for the use of an artificial intelligence, algorithm, or other software tool for the purpose of utilization review for health and accident insurance.
This bill would regulate the use of artificial intelligence, algorithms, and other software tools in utilization review and utilization management for health care services. It adds new sections to the Public Health Law and Insurance Law requiring that any such tool used by a utilization review agent or insurer be based on an individual enrollee’s or insured’s clinical history, the requesting provider’s clinical information, and other relevant medical record information, rather than relying solely on group datasets. The bill also requires that these tools comply with applicable state and federal law, be open to audit and compliance review, be periodically reviewed for accuracy and reliability, and be disclosed in written policies and procedures.
A central feature of the bill is that AI or similar software may not deny, delay, or modify health care services based in whole or in part on medical necessity. Instead, medical necessity determinations must be made by a licensed physician or other qualified licensed health care professional who reviews the provider’s recommendation and the patient’s individual clinical circumstances. The bill defines artificial intelligence broadly and applies these requirements to prospective, retrospective, and concurrent utilization reviews of covered health care services. It also includes privacy, nondiscrimination, and patient-harm safeguards, and ties implementation to federal rules and guidance from the U.S. Department of Health and Human Services.
The bill’s impact on state law would be to create a new regulatory framework for insurers, disability insurers, health care service plans, and utilization review agents operating in New York. It would amend both the Public Health Law and the Insurance Law to limit automated decision-making in coverage review and to preserve clinician judgment in medical necessity determinations. It would also authorize the department to issue implementation guidance, enter into contracts for administration, and act only to the extent federal approvals are obtained and federal financial participation is not jeopardized.
The general sentiment reflected by the bill text is strongly precautionary and consumer-protective, favoring human oversight over automated systems in health coverage decisions. Although there are no committee transcripts or recorded votes provided, the structure of the bill suggests support for restricting potentially opaque or biased AI-driven utilization review practices, especially where they could affect access to care. The bill appears aimed at preventing denials or delays caused by automated tools and at ensuring transparency, fairness, and accountability.
The main points of contention likely involve the scope of the AI restrictions and the operational burden on insurers and utilization review entities. Potential concerns include whether the bill goes too far in limiting the use of automation, how “medical necessity” determinations would be handled in practice, and whether the required audits, disclosures, and compliance reviews could increase administrative costs. Another possible issue is the bill’s reliance on future federal guidance, which could affect implementation timing and regulatory certainty.
The bill would add new provisions to the Public Health Law and Insurance Law governing utilization review and utilization management when artificial intelligence, algorithms, or other software tools are used in coverage decisions. It would require individualized clinical review, prohibit AI from making medical necessity determinations or directly denying, delaying, or modifying services on that basis, and impose nondiscrimination, auditability, disclosure, and data-use safeguards on affected plans and insurers. The bill would also authorize department guidance and contracting for implementation, subject to federal approval and federal funding conditions.
The bill’s overall tone is protective of patients and skeptical of automated coverage decisions. Even without recorded debate or votes, the text indicates a policy preference for human clinical judgment, transparency, and oversight over AI-driven utilization review. The likely sentiment among supporters would be that the bill prevents unfair denials and bias, while opponents or cautious stakeholders may view it as overly restrictive or administratively difficult for insurers to implement.
The likely areas of contention are the bill’s limits on automated decision-making, especially the prohibition on AI denying, delaying, or modifying services based on medical necessity, and the requirement that only licensed clinicians make those determinations. Insurers and utilization review entities may object to compliance costs, audit requirements, and constraints on using predictive tools to manage care. Supporters, by contrast, would emphasize patient protections, individualized review, privacy, and anti-discrimination safeguards, particularly where AI systems could rely on group data or opaque criteria.