CTeL Encourages Balanced AI Regulations in Healthcare, Across the Board.
Advocating for balanced AI regulations in healthcare is critical to ensuring that we, as a digital health collective, unlock the full potential of this transformative technology. Artificial intelligence (AI) offers unparalleled opportunities to improve patient outcomes, increase access to care, and reduce healthcare costs, particularly in telehealth services. From enhancing diagnostic accuracy to streamlining administrative tasks, AI can enable healthcare providers to deliver faster, more personalized, and more efficient care.
However, overly restrictive regulations could hinder innovation and limit access to these vital advancements, particularly for underserved communities that benefit most from expanded telehealth services. Balanced policies that promote innovation while safeguarding patient safety, data privacy, and ethical standards are essential to realizing the full promise of AI. With AI, we can expand access to care in rural areas, reduce costly hospitalizations, and improve the overall efficiency of our healthcare system. Advocating for thoughtful, balanced AI regulations ensures that we continue to progress toward a healthcare future that is more accessible, equitable, and effective for all.
“Introduced on January 19, 2023, SB 255, creates an omnibus consumer privacy law based on a composite of the Colorado Privacy Act, Connecticut Data Privacy Act, and Virginia Consumer Data Protection Act. In particular, the bill sets out rules for profiling and automated decision-making. Specifically, the bill enables individuals to opt-out of “in furtherance of solely automated decisions that produce legal or similarly significant effects concerning the consumer.”
The Benefits of AI in Healthcare: Improving Care, Reducing Costs, and Expanding Access
Artificial intelligence (AI) is revolutionizing healthcare by significantly enhancing diagnostic accuracy, reducing errors, expanding access to care, and lowering healthcare costs. One of AI's most profound impacts is in improving diagnostics. AI-powered tools, such as machine learning algorithms, can analyze vast amounts of data faster and more accurately than human clinicians. For example, a study published in Nature Medicine found that an AI model diagnosed breast cancer with greater accuracy than human radiologists, reducing false negatives by 9.4% and false positives by 5.7% (McKinney et al., 2020). These advancements in diagnostic accuracy are especially valuable in preventing misdiagnoses and ensuring early detection of diseases like cancer, heart conditions, and diabetes, leading to better patient outcomes and more effective treatment plans.
“Medical errors account for an estimated 250,000 deaths annually in the U.S., making it the third leading cause of death ”
AI also plays a crucial role in reducing human error in clinical decision-making and administrative tasks. Medical errors account for an estimated 250,000 deaths annually in the U.S., making it the third leading cause of death (Makary & Daniel, 2016). AI-powered systems help mitigate these risks by providing real-time decision support, automating routine tasks, and flagging potential mistakes before they happen. For instance, AI-driven platforms can cross-reference patient data with vast medical literature and guidelines, ensuring clinicians have the most accurate, up-to-date information to guide their decisions. Additionally, in administrative functions, AI reduces errors in billing and patient record management, saving both time and money for healthcare systems.
Another key benefit of AI is its ability to expand access to care, particularly in underserved and rural areas. Telehealth platforms, enhanced by AI, allow patients to access high-quality care remotely, regardless of geographical barriers. AI-powered diagnostic tools and virtual assistants can assist patients in managing chronic diseases, conducting virtual consultations, and monitoring their health at home, reducing the need for in-person visits. This is particularly impactful in rural communities, where healthcare provider shortages are severe. According to the Health Resources and Services Administration (HRSA), over 65 million Americans live in areas with insufficient access to primary care (HRSA, 2021). AI-driven telehealth can bridge this gap by bringing specialized care to patients who otherwise might not have access.
Finally, AI contributes to significant cost reductions in healthcare. By streamlining workflows, optimizing treatment plans, and reducing hospital readmissions, AI can save healthcare systems billions of dollars annually. McKinsey & Company estimates that AI could save the U.S. healthcare industry up to $150 billion per year by 2026 (Snyder et al., 2019). These cost savings, combined with improved patient outcomes and greater accessibility, make AI a game-changer in healthcare’s future.
“McKinsey & Company estimates that AI could save the U.S. healthcare industry up to $150 billion per year by 2026.”
Advocating for thoughtful, balanced regulation is essential to maximizing the benefits of AI in healthcare. By addressing concerns such as data privacy and bias while encouraging innovation, we can ensure that AI improves patient outcomes, expands access to care, and reduces costs, particularly in telehealth, where AI holds immense promise for the future.
CTeL’s AI Blue Ribbon Collaborative
So what is CTeL doing to help? We’re glad you asked!
In 2024, CTeL launched its AI Blue Ribbon Collaborative, a pioneering initiative that assembles a distinguished panel of experts to act as an independent resource for clinical and legal questions regarding the integration of AI and healthcare. This collaboration will work to establish clear standards, rules of engagement, and best practices that ensure AI technologies are used safely, ethically, and effectively. By advancing policies that promote innovation while safeguarding patient privacy and safety, the AI Blue Ribbon Collaborative aims to expand access to care for millions, making high-quality, AI-enhanced healthcare a reality for underserved communities and beyond.
AI in healthcare, particularly in the telehealth space, must adhere to the core principles outlined in President Biden’s Executive Order on AI, referred to as FAVES: fairness, accountability, viability, effectiveness, and safety. These guiding principles ensure that AI technologies are developed and deployed responsibly, maximizing their potential to improve patient outcomes while protecting individuals and communities.
Fairness: In healthcare, AI systems must operate without bias, ensuring equitable access to services across diverse populations. Whether diagnosing patients or determining treatment plans, AI must support fairness, particularly for historically underserved communities. AI’s ability to process large datasets can help overcome disparities by delivering consistent, data-driven care, but fairness must be prioritized to avoid reinforcing existing inequalities.
Accountability: AI in healthcare requires robust oversight mechanisms. From developers to healthcare providers, everyone involved in AI’s lifecycle must be accountable for ensuring its safe, ethical, and compliant use. This principle will guide the creation of clear standards and regulatory frameworks to guarantee that AI in healthcare aligns with existing laws, such as HIPAA, and ensures protection of sensitive patient data.
Viability: AI-driven solutions must be practical and scalable within the healthcare system. This means technologies must demonstrate long-term sustainability in terms of both cost and functionality. By integrating AI to assist physicians, reduce administrative burdens, and optimize workflows, AI solutions will enhance healthcare delivery while ensuring the financial viability of healthcare systems.
Effectiveness: To gain widespread adoption, AI technologies must prove their effectiveness in improving care quality and outcomes. This includes enhancing diagnostic accuracy, personalizing treatment plans, and improving operational efficiencies. Proven effectiveness will increase clinician trust and patient confidence in AI-enabled healthcare solutions.
Safety: Ensuring the safety of patients is paramount in AI deployment. Rigorous testing, validation, and continuous monitoring of AI tools will ensure they enhance care without introducing harm. AI systems must be transparent in their decision-making processes and subject to regulatory standards that protect patient welfare.
CTeL’s AI Blue Ribbon Collaborative will ensure that these FAVES principles are at the core of any AI initiatives in healthcare, helping to establish a balanced regulatory framework that promotes both innovation and patient safety. By aligning with these principles, AI can truly transform healthcare, improving outcomes and expanding access to care for millions.
As legislators are working to grasp and understand the capabilities of emerging technologies, we encourage lawmakers to allow room for growth, advancement, and openness to what technologies can do today and in the future.
References:
Health Resources and Services Administration (HRSA). (2021). Designated Health Professional Shortage Areas Statistics. https://data.hrsa.gov/topics/health-workforce/shortage-areas
Makary, M. A., & Daniel, M. (2016). Medical error—the third leading cause of death in the US. BMJ, 353, i2139. https://doi.org/10.1136/bmj.i2139
McKinney, S. M., Sieniek, M., Godbole, V., Godwin, J., Antropova, N., Ashrafian, H., ... & Suleiman, Y. (2020). International evaluation of an AI system for breast cancer screening. Nature Medicine, 26(6), 914–919. https://doi.org/10.1038/s41591-020-0832-6
Snyder, J., Dhar, V., & Malhotra, A. (2019). The economic impact of artificial intelligence in healthcare. McKinsey & Company. https://www.mckinsey.com/industries/healthcare-systems-and-services
New Hampshire: SB 255