The Necessity of Sector-Specific Regulations in Healthcare: Why Horizontal Regulations Fall Short

Horizontal AI regulations are laws made to cover many industries, not just one. The goal is to have rules that any company can follow when using AI. At first, this seems simple, but these rules miss some important problems in healthcare.

Healthcare in the U.S. has many strict rules because it deals with very private patient information, health risks, and ethical questions. Laws like HIPAA focus on keeping patient information safe. When AI is added, things get more complicated. Horizontal regulations often miss these extra challenges.

The European Union started the Artificial Intelligence Act in 2024. This law tries to balance new ideas with safety and ethics. Still, experts like Hannah van Kolfschooten and Janneke van Oirschot say this Act does not fully meet healthcare needs. It is made to cover many sectors but lacks details needed for healthcare AI risks. This is similar to debates in the U.S. about whether general AI laws like the Algorithmic Accountability Act or California’s Assembly Bill 331 are enough for healthcare AI.

Why Healthcare Needs Sector-Specific AI Regulations

Healthcare AI is different and more complex than AI in other areas for several reasons:

• Sensitive Data and Privacy Needs
  Healthcare has protected health information (PHI) that must be kept secret. AI systems handling this data need very strict rules to stop misuse or leaks. Patient details such as health history are important but must be safe under laws like HIPAA.
• Safety and Ethical Concerns
  AI can influence diagnoses, treatments, and emergencies. If AI makes a mistake or shows bias, it can cause serious problems. Healthcare needs special rules to manage these risks and keep things accurate.
• Compliance with Healthcare-Specific Rules
  Healthcare AI may work like medical devices. These devices are regulated by the FDA with Medical Device Regulation (MDR) and In Vitro Diagnostic Regulation (IVDR). AI rules need to fit with these, so no conflicts or gaps happen.
• Complexity of AI Uses
  Healthcare AI is used in many different ways, such as emergency call triage, insurance checks, diagnostics, and remote monitoring. Each use has its own risks and needs clear rules.

The Challenges of Horizontal Regulation in U.S. Healthcare

Some U.S. AI laws like the Algorithmic Accountability Act want AI impact checks, mainly to stop bias and discrimination. California’s Assembly Bill 331 needs transparency and impact reviews for AI, including healthcare. But these laws do not work well with existing healthcare laws, causing overlaps or gaps.

Horizontal laws are made for general use and do not think deeply about healthcare’s needs. For example:

• Protecting patient information is key for good healthcare decisions. But general laws may not solve privacy and bias problems well.
• Risks with AI in emergency calls or diagnosis need special knowledge and care.
• Without specific rules, healthcare groups might break laws or not get enough protection from general AI laws.

Airlie Hilliard, an expert on AI rules, says healthcare needs AI laws that are clear and specific. These laws should stop harm, keep data private, treat patients fairly, and allow the correct use of patient data for care.

How Sector-Specific Regulations Can Benefit U.S. Healthcare Providers

For those running healthcare in the U.S., clear AI rules made just for healthcare can help in many ways:

• Improved Patient Safety: Clear rules for testing and using AI tools can lower mistakes and keep patients safer.
• Transparency and Accountability: Healthcare-specific rules can ask AI makers and providers to keep clear records, which helps find and fix problems fast.
• Compliance with Multiple Laws: AI rules made to fit with HIPAA, FDA, and others reduce confusion and paperwork.
• Encouragement of Innovation: Clear rules on data and how systems work together can support new ideas while protecting patients.
• Risk Mitigation: Specific methods for checking risks and managing data help healthcare avoid legal and other problems.

AI and Workflow Automation in Healthcare: Relevance to Front-Office Operations

Besides health care, AI matters a lot in the office work of healthcare. This includes phone calls, scheduling, patient questions, and answering services. AI can make these tasks better and faster.

For example, Simbo AI focuses on automating front-office phone tasks. This AI handles routine calls so staff can do more important work. It helps patients by reducing wait times. Calls for appointment confirmations, insurance checks, or urgent requests are handled quickly and correctly by AI. This leads to smoother work and less stress for office staff.

But using AI this way also brings concerns that need careful rules:

• Protecting Patient Information: Phone systems collect sensitive data that must be kept safe.
• Ethical Use of AI: AI needs to understand what patients say and send urgent issues to staff.
• Integration With Healthcare Systems: AI tools must work with healthcare computers and records properly.
• Ensuring Accessibility: AI systems should be easy to use for all patients, including people with disabilities or language difficulties.

Healthcare-specific rules for AI in these areas can help keep patients safe and treated fairly. They also guide healthcare workers on how to manage data, check systems, and control risks when using AI for office work.

Looking Toward the Future: The Path for U.S. Healthcare AI Regulation

The EU’s AI Act, which started in August 2024, shows why we need rules made for each sector. It stresses being clear, responsible, and managing risks, especially for healthcare AI like emergency call handling. Writers like Hannah van Kolfschooten and Janneke van Oirschot say the Act helps safety and new ideas but still needs extra healthcare rules to protect patients better.

In the U.S., lawmakers should notice this. They need to make AI laws that fit with healthcare rules like HIPAA and FDA device policy. Laws should require risk checks, ongoing watching, data safety, and fair AI use.

Healthcare leaders must understand these changing rules. They should act early to use AI that follows the law, especially in patient care and office tasks. Companies like Simbo AI show how AI can help in healthcare offices but must also follow or help create clear, healthcare-specific rules.

By going beyond broad AI rules to health-focused ones, the U.S. can better protect patients, support healthcare progress, and guide providers to use AI safely.

Summary

Artificial Intelligence is growing in U.S. healthcare, both in medical care and office work. The current broad AI rules work in some ways but do not fit healthcare’s special needs. From protecting private data to managing risks in patient care and emergencies, healthcare-specific AI rules are needed. They give healthcare leaders clear instructions to keep patients safe, follow laws, and use AI well.

Government leaders should create AI rules that work with existing healthcare laws. Healthcare groups should watch rules closely and pick AI tools that keep data safe, work clearly, and can be trusted. Companies like Simbo AI show the benefits of AI in healthcare offices but also show why strict rules are important to protect patients.

Balancing new technology and clear rules will be important for using AI in U.S. healthcare in the future.