Artificial Intelligence (AI) is impacting industries across the globe, transforming conventional ways in which organizations operate, provide services, and make decisions. This rapid transformation is felt across sectors, particularly the healthcare industry, where AI is accelerating clinical diagnosis, providing personalized treatment and medicine, improving patient engagement, unlocking operational efficiency, and much more.
As AI sweeps its way into the healthcare industry and workflow, ensuring the security of protected health information (PHI) becomes a non-negotiable requirement to demonstrate compliance with the Health Insurance Portability and Accountability Act (HIPAA), a law tasked with protecting sensitive PHI from unauthorized disclosure, providing patients’ rights over their healthcare records, and ensuring the secure exchange of patient data.
This guide explores the impact of AI in the healthcare industry, the rules AI developers and deployers must follow, and provides an AI HIPAA compliance checklist.
Why HIPAA is Critical for AI in Healthcare
HIPAA, enacted on August 21, 1996, is a US federal law that mandates strict privacy and security requirements for Protected Health Information (PHI). It forms the basis for securing sensitive patient health data by requiring covered entities, such as healthcare providers and their business associates, to implement administrative, physical, and technical safeguards that limit access to PHI, prevent unauthorized data disclosure, and ensure the confidentiality, integrity, and availability of patient healthdata across multiple systems and workflows.
A. AI Utilizes PHI
HIPAA is more than just critical for AI in healthcare, as AI systems thrive on massive volumes of patient data to provide improved patient healthcare services, generate valuable insights, automate workflows, and much more. During this accelerated performance and capability, AI systems end up processing PHI, and that’s where HIPAA begins to apply immediately in an effort to secure patients’ sensitive data from being mishandled or utilized without consent.
B. AI Intensifies Privacy Risks
Since AI is data-hungry by nature, if PHI ends up being processed by the AI model, it can escalate into a massive data exposure. This nightmare is highly likely when an individual ends up feeding PHI to an unregulated AI tool that processes that information, and it ends up outside the secure environment. HIPAA ensures individuals dealing with PHI are aware of its privacy and security requirements, despite the promising advantage of AI tools.
C. HIPAA Mandates Security Controls
To begin with, there’s no way around providing healthcare services without ensuring HIPAA compliance. With that in mind, healthcare providers and associates have to embed security measures as a core part of PHI processing, storing, and sharing. HIPAA’s Security Rule mandates these entities to implement role-based access controls, data encryption, regular audits and risk assessments, a robust incident response plan, and much more.
D. AI Providers are Subject to HIPAA
AI providers whose platform collects, processes, stores, and shares PHI are automatically subject to HIPAA regulations. Such providers must comply with all HIPAA-related security obligations and sign a Business Associate Agreement (BAA) certifying that they’ll ensure the privacy and security of PHI in compliance with HIPAA privacy and security rules.
E. HIPAA Minimizes Regulatory Noncompliance Risks
HIPAA isn’t just an act on paper. It’s a comprehensive regulation that demands covered entities to comply with each requirement to secure PHI. Noncompliance with HIPAA regulations can lead to hefty noncompliance penalties from the HIPAA regulatory authority, the U.S. Department of Health and Human Services (HHS) Office for Civil Rights (OCR).
HIPAA Rules AI Must Follow
AI developers and deployers must ensure that their AI tool ensures the following:
A. The Privacy Rule
AI providers must ensure sensitive PHI protection by minimizing its usage and disclosure. This ensures that PHI is not shared or exposed through AI tools unless it’s allowed under HIPAA.
B. The Security Rule
AI providers must develop AI systems keeping security as a first priority rather than an afterthought. AI systems must be designed with state-of-the-art security controls such as multi-factor authentication, role-based access controls, regular risk assessments and audits, and secure storage and transfer.
8 Steps to Keep AI HIPAA-Compliant
Here are the practical steps to keep AI-HIPAA compliant:
1. Data Minimization and Purpose Limitation
AI providers must ensure that they collect only the minimum personal data necessary for a specific, defined goal and use that data only for that purpose.
2. Data Retention and Deletion
AI providers must reduce liability and storage costs by defining how long and where PHI will be stored, along with how and when it will be deleted once it no longer serves its collected purpose.
3. Identify PHI in the AI Model
At its core, the AI model is running on data fed to the model. The key is to identify where PHI resides, whether it’s in the chat inputs, input documents, storage server, outputs, etc.
There’s no need to reinvent the wheel, especially when a HIPAA-compliant AI tool is already available. Just ensure that the AI tool is certified by an accredited body and prioritizes data encryption, access controls, audits, etc.
5. Engage in a Business Associate Agreement (BAA)
Whether an AI model is developed internally or sourced externally, a BAA is crucial for demonstrating compliance. The BAA outlines permitted PHI usage, security, incident response, and subcontractor requirements, certifying the healthcare organization’s capability of honoring HIPAA requirements.
6. Conduct Risk Assessments
Under the HIPAA Security Rule, covered entities and business associates are required to conduct risk assessments to identify and mitigate evolving risks. For AI, this includes the evaluation of risks like data leaks and model inversion attacks. This ensures top-notch data confidentiality, integrity, and availability.
7. Data Encryption and Access
Data encryption is the first priority organizations should undertake, where PHI is encrypted at rest (in databases and logs) and in transit (between your application and AI’s API). Additionally, PHI access should be limited to authorized individuals, minimizing inadvertent data exposure.
8. Data Lineage
Data moves through on-premises, cloud, and multi-cloud environments at lightning speeds. Data lineage helps provide a traceable, well-documented history of PHI as it traverses across systems, borders, and continents.
Automate Compliance with Securiti DSPM
As regulatory pressure increases and data environments grow more complex, organizations can no longer rely on manual methods to ensure compliance. DSPM offers a proactive, automated, and scalable solution to maintaining a continuous data security and privacy posture, not just for HIPAA, but for any current or future regulation.
Securiti's Data Command Center (rated #1 DSPM by GigaOM) provides a built-in DSPM solution, enabling organizations to secure sensitive data across multiple public clouds, private clouds, data lakes and warehouses, and SaaS applications, protecting both data at rest and in motion.
With Securiti, organizations can leverage contextual data intelligence and controls to discover and classify data, minimize ROT (Redundant, Obsolete, and Trivial) data risk, reduce misconfiguration vulnerabilities, prevent unauthorized data access, understand data flow, and enforce consistent security controls across the data journey, including real-time streaming data, while also managing compliance and breach risk.
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