Hogan Lovells 2024-2025 AI Trends Guide - Flipbook - Page 23
Industry must engage to ensure patient access to AI-enabled health
innovations
AI-enabled technologies have demonstrated enormous
potential for health care, fueling advances in areas as varied
as drug development, software-as-a-service, and analysis
of medical images. Importantly, AI systems can address
pressing issues such as health care workforce shortages
and improving access for underserved communities.
Notwithstanding these promises, health AI technologies
continue to face obstacles in reaching patients.
Global developments including the AI Act (EU), the Biden
Executive Order on AI (U.S.), and Colorado’s AI Act (the first of
its kind at the state level) are industry-agnostic but will likely
present unique challenges for AI developers in the health
sector, including the possibility of duplicative regulation or
conflicting regulatory obligations. Policymakers continue to
face a steep learning curve and industry perspectives are vital
to advance appropriate regulations that both foster innovation
while protecting patients and users from the negative impacts
that can come with the promise of AI.
Regulators of products that contain AI have decades-long
experience authorizing and overseeing software algorithms
but, as algorithms have become more complex and are
increasingly used to diagnose and treat patients, regulators
are challenged to keep up with the pace of innovation and
regulate the products using the existing frameworks. Further,
industry strives to meet the expectations of regulators, which
can vary across geographies for the same product; lending
support for harmonization measures where possible.
Additional
resources
AI developers seeking to commercialize also continue
to struggle within the existing legacy coverage and
reimbursement pathways. While many stakeholders are
urging reform, the current coverage and payment framework
requires extensive coordination among multiple stakeholders,
raising vexing questions, including: Can existing valuation
models and processes be utilized to create appropriate
reimbursement rates AI services? Are there non-traditional
payment or other incentive models which may ensure patient
access by, for example, permitting temporary transitional
coverage or prioritizing preventive care? And, does the
innovator have sufficient resources to continue to provide
access while acceptable reimbursement is accessed?
Finally, AI enabled systems and tools are dependent on their
lifeblood, which is data—data to develop them, data to refine
them, data to innovate them, and data to control them. At
the same time, the issues around patient data are growing
in complexity as regulators, patients, and clinicians become
better equipped to understand the challenges and risks of
utilizing patient data, especially in the context of AI systems.
Stakeholders with AI-enabled systems and tools currently
under development must stay engaged to ensure patient
access to the benefits of their innovations. Learn more about
Hogan Lovell’s leadership through the AI Healthcare Coalition
to engage with policymakers on these issues.
Spotlight
Life Sciences and Health Care
Brochure 2024 – Digital Health and AI
Authors
Melissa Bianchi
Partner
Washington, D.C.
Cybil Roehrenbeck
Partner
Washington, D.C.
Fabien Roy
Partner
Brussels
Jodi Scott
Partner
Denver
