Analyzing the Impact of Federal Executive Orders on Establishing Governance and Transparency Standards for AI Deployment in Healthcare Settings

On October 30, 2023, President Biden signed an Executive Order that aims to create rules for using AI safely across different areas, including healthcare. The order gives federal agencies directions to control AI use and lower risks, while encouraging responsible development.

The Department of Health and Human Services (HHS), which regulates healthcare, must set up an AI Task Force within 90 days of the order. This group will make a plan within a year to guide AI use in healthcare. Their plan will cover safety, fairness, privacy, and openness. The order also tells HHS to start an AI Safety Program by October 2024. This program will help find, track, and fix clinical AI mistakes to keep patients safe.

These federal rules are a step toward controlling AI tools, especially those that use private health information or affect medical decisions. The goal is to prevent harm, protect privacy, and make sure AI is fair in healthcare settings.

Governance and Compliance: Preparing Healthcare Organizations for AI Integration

Healthcare managers and owners must get ready to follow the rules in the Executive Order and other laws like HIPAA. HIPAA already sets strict limits on handling private health information (PHI). Using AI adds new challenges in managing this data.

The Executive Order focuses on several main rules:

• Safety and Security: AI should have strong protections, especially against hacking or attacks that trick AI into making wrong choices or leaking data.
• Transparency: Hospitals and clinics must explain clearly how AI uses data, makes decisions, or produces results. This helps patients and workers trust AI and meets future rules about labeling AI content.
• Equity and Non-Discrimination: AI systems should be checked often to avoid bias and treat all patients fairly. This follows federal civil rights laws and needs regular reviews across different patient groups.
• Human Oversight: People must still watch how AI works, check its accuracy, and step in if mistakes happen or unsafe results appear.

The HHS AI Task Force and Safety Program will put these ideas into action. Healthcare groups should expect more advice from the Office of the Inspector General (OIG) about following AI risk rules in their specific areas.

HIPAA and AI: Challenges in Privacy and Security

HIPAA’s Privacy and Security Rules are important for protecting patient data. Adding AI requires changes to meet these rules under new situations. HIPAA’s Security Rule has three types of protections that apply to AI:

• Administrative safeguards: These are rules and steps to handle AI risks and keep rules, like training staff who use AI.
• Physical safeguards: These protect the hardware and places where AI data is stored and processed.
• Technical safeguards: These secure AI data itself through access controls, encryption, and checking.

AI often needs to use a lot of PHI to work well. But HIPAA requires the “minimum necessary” rule, meaning AI can only use the data it really needs. Tracking how AI uses PHI is very important to follow the law and avoid accidental exposure of private information.

Also, AI brings new cybersecurity risks. Hackers might fool AI or use AI to launch stronger cyberattacks. IT managers in healthcare must learn these dangers and put in stronger protections.

Transparency and Accountability in AI Use

Besides privacy and security, being open about AI use is important. Healthcare groups will need to clearly say how AI is used, including:

• Where the data the AI uses comes from
• How AI makes decisions or predictions
• What AI results affect patients or administration
• Whether content or messages are made or helped by AI

Labeling AI-made content helps patients and staff understand what technology is involved in their care. This openness can also lower legal risks related to unfair practices under the Federal Trade Commission (FTC) Act, which holds healthcare groups responsible for wrong uses of personal data or false claims about AI.

As rules develop, keeping good records and doing audits of AI systems may become normal practice. This includes listing all AI tools, what they do, and checking risks related to PHI and clinical effects.

AI Governance Frameworks: The Role of NIST’s Risk Management Framework

The National Institute of Standards and Technology (NIST) released an AI Risk Management Framework (RMF) in 2023. This gives healthcare groups a clear way to handle AI risks with four main steps:

• Govern: Set rules and leadership for AI oversight.
• Map: Find AI risks in healthcare settings.
• Measure: Check AI’s safety, fairness, and performance.
• Manage: Use controls to lower or fix risks found.

NIST’s AI Playbook also gives practical advice that fits well with federal rules from the Executive Order. By using NIST’s framework, clinic managers and IT staff can watch AI closely, lower legal risks, and get ready for new government rules.

AI and Workflow Digitization in Healthcare Front Offices

One of the fastest ways AI affects healthcare is in phone automation and answering systems. Companies like Simbo AI work in this area. Front-desk tasks such as scheduling, appointment reminders, and patient questions rely on good communication. AI can help here by:

• Giving patient support 24/7 without extra staff
• Handling routine requests to cut wait times and fewer calls
• Linking with Electronic Health Records (EHR) to check patient info safely
• Keeping privacy rules by controlling data access and use

This improves how clinics run by letting staff focus on harder tasks instead of simple calls. It also lowers human mistakes in taking information or making appointments, helping patient happiness and cutting missed visits.

But AI tools in front offices must still meet safety and openness rules mentioned before. Many managers forget that automation tools need good AI risk checks to avoid data leaks or mistakes with patient info. Compliance teams must cover not just AI in clinics but also these office systems.

The Executive Order for safe AI use encourages clinics to add these tools carefully, keeping patient data safe and following rules.

Preparing for Future AI Regulations and Healthcare Practice Implications

The Executive Order sets the base rules, but new laws are coming to control AI more. For example, the Artificial Intelligence Research, Innovation, and Accountability Act and AI Labeling Acts may require clinics to report on AI use and follow standards like NIST’s RMF.

Healthcare leaders should take early steps, such as:

• Listing all AI tools in their clinics
• Tracking AI access to sensitive patient data
• Training staff on new AI laws and rules
• Working with legal teams to update compliance plans for AI
• Watching for advice from groups like OIG, FTC, and the HHS AI Task Force

As AI becomes part of care and admin work, managing risks and following new standards will be key to keeping patient trust, avoiding fines, and improving service quality.

Summary of Federal Initiatives and their Impact on U.S. Healthcare Organizations

The Executive Order signed in 2023 is an important moment for AI rules in healthcare. It asks the Department of Health and Human Services to make plans that balance new technology with patient safety, privacy, and fairness. For owners, administrators, and IT staff, using AI means following strong rules, handling data openly, and keeping human checks on AI results.

All healthcare groups using AI—including companies like Simbo AI—must change how they work and follow laws to fit these new federal rules. The changing legal environment means acting early to handle AI risks, protect patient data, and treat patients fairly across the United States.

This increasing focus on AI rules will keep shaping how AI is used in all kinds of healthcare places. Clinic leaders should stay aware of changes in AI laws and tools and start using best practices before they become required. With clear rules and openness, healthcare groups can use AI safely to improve patient care and office efficiency.