In 2024, more doctors started using AI, almost twice as many as before, says a survey by the American Medical Association (AMA). At the same time, data breaches in healthcare are growing, which raises concerns about patient privacy and safety when using AI. The biggest healthcare breach in 2024 affected 190 million people, according to Change Healthcare, Inc. This shows how much harm can happen if AI systems are not well protected.
AI in healthcare works in different ways. It includes Clinical Decision Support Systems (CDSS), tools that help with medical images, and systems that automate office tasks. All these rely on electronic health records (EHRs) and sensitive data. This makes it easier for information to be accidentally shared or stolen if not properly guarded.
HIPAA’s Privacy and Security Rules are made to protect health information. Still, using AI makes following these rules harder. Healthcare groups must carefully create policies, choose vendors, and run processes that lower risks without stopping new technology.
Healthcare providers must have clear Business Associate Agreements with any AI vendors that handle protected health information (PHI). These agreements make sure vendors follow HIPAA rules, explain exactly how PHI can be used, and forbid using data for other purposes like training AI without patient permission. They also require vendors to quickly report breaches, so hospitals can act fast.
If providers don’t keep strong BAAs, they might face legal trouble and fines.
HIPAA lets providers share PHI without patient approval only for treatment, payment, and healthcare operations (TPO). Using data for anything else, including improving AI, needs the patient’s clear consent. If consent is not given, this breaks HIPAA’s Privacy Rule.
Providers must tell patients how AI is used and offer ways to opt out when possible. This rule is both a legal and ethical issue.
AI adds extra technical challenges, especially for securing data used by AI systems. This calls for better controls and constant checking.
Training staff about AI risks is important to avoid compliance mistakes. One big problem is called “shadow IT,” where workers use AI software not approved by the organization. This ignores security rules and raises chances of leaks or breaches.
Healthcare providers should teach employees which AI tools are allowed and stress using multi-factor authentication and safe data handling.
Choosing AI vendors carefully helps lower risks. The selection should focus on cybersecurity and legal compliance. Healthcare providers should:
Doing all this reduces legal risks and helps patients trust that their data is handled carefully.
More healthcare offices are using AI to automate tasks like phone calls and scheduling. For example, Simbo AI helps manage front-office calls to cut down on volume and improve patient access. But these AI tools handle PHI during calls and appointments, so HIPAA rules apply.
To manage compliance when using AI automation:
AI can make work easier but healthcare providers must keep watch to avoid privacy problems.
Regular risk assessments help find weaknesses related to AI data use. They should show how data moves through AI, where dangers might come from, and how well the protections work.
Providers should keep careful records of these assessments, security steps taken, staff training, and any security issues. This helps with audits and shows they are meeting HIPAA rules. It also points out where improvements are needed.
Healthcare providers must follow changing rules about AI, privacy, and patient rights. Important rules include:
Providers need to keep up with these rules to use AI in ways that respect patient privacy and legal requirements.
New compliance approaches focus on protecting the data itself, not just the network. Data-centric security means PHI is safe no matter where it is stored or used. This includes:
This approach fits well with HIPAA’s technical rules and allows AI use without risking patient data security.
Managing AI-related HIPAA risks needs many actions all at once. This includes strong vendor partnerships, security practices, and staff education. Healthcare leaders should:
Using these steps, healthcare providers can use AI to help patients and run smoothly while keeping patient data safe and private.
As AI grows in healthcare—from helping with diagnoses to automating office work—the duty to handle HIPAA risks lies with healthcare providers. AI deals with large amounts of sensitive data, so providers need strong privacy law compliance, clear vendor contracts, technical safeguards, and ongoing staff training. Those who build compliance into each step of adopting AI can lower the chance of breaches, avoid fines, and protect patient information well.
This article aims to guide healthcare leaders in the United States about the challenges AI brings to following HIPAA rules. It shows that protecting patient privacy and improving healthcare with technology must go hand in hand.
The primary categories include Clinical Decision Support Systems (CDSS), diagnostic imaging tools, and administrative automation. Each category processes protected health information (PHI), creating privacy risks such as improper disclosure and secondary data use.
BAAs legally bind AI vendors to use PHI only for permitted purposes, require safeguarding patient data, and mandate timely breach notifications. This ensures vendors maintain HIPAA compliance when receiving, maintaining, or transmitting health information.
PHI can be shared without patient authorization only for treatment, payment, or healthcare operations (TPO). Any other use, including marketing or AI model training involving PHI, requires explicit patient consent to avoid violations.
Breaches expose sensitive patient data, disrupt IT systems, reduce availability and quality of care by delaying appointments and treatments, and risk patient safety by restricting access to critical PHI.
Careful vendor selection is essential to prevent security breaches and legal liability. It includes requiring BAAs prohibiting unauthorized data use, enforcing strong cybersecurity standards (e.g., NIST protocols), and mandating prompt breach notifications.
Employees must understand AI-specific threats like unauthorized software (‘shadow IT’) and PHI misuse. Training enforces use of approved HIPAA-compliant tools, multi-factor authentication, and security protocols to reduce breaches and unauthorized data exposure.
Covered entities and business associates must ensure PHI confidentiality, integrity, and availability by identifying threats, preventing unlawful disclosure, and ensuring employee compliance with HIPAA law.
Secondary use of PHI for AI model training requires explicit patient authorization; otherwise, such use or disclosure is unauthorized and violates HIPAA, restricting vendors from repurposing data beyond TPO functions.
Providers should enforce rigorous vendor selection with strong BAAs, mandate cybersecurity standards, conduct ongoing employee training, and establish governance frameworks to balance AI benefits with privacy compliance.
Short breach notification timelines enable quick response to incidents, limiting lateral movement of threats within the network, minimizing disruptions to care delivery, and protecting PHI confidentiality, integrity, and availability.
Simbo is using AI agents to automate all phone related workflows. Connect now to know more.
Schedule AI Agents Demo Now© Since 2019, Simbo AI.
