The 2024-2030 Federal Health IT Strategic Plan emphasizes a critical priority for the future of healthcare: ensuring the security and portability of electronic health information (EHI). This vision aims to empower individuals with control over their health data while enhancing trust in the systems that store, process and share this sensitive information.
As patient data becomes more accessible and interoperable across platforms, healthcare organizations face evolving cybersecurity challenges, particularly as clinical AI becomes integrated into diverse areas of the health system. A robust, multi-layered approach to cybersecurity is essential for managing these risks effectively and ensuring sustainable, secure healthcare delivery.
Building Trust Through Secure, Interoperable Health IT
As systems become more interconnected, the healthcare sector must adopt strong cybersecurity measures to protect this information from emerging threats. Risk management frameworks become invaluable here, serving as the operational foundation that healthcare providers and administrators can rely on to safeguard patient data.
Guidance frameworks like the NIST AI Risk Management Framework (AI RMF) and ISO/IEC 23894 provide actionable guidance to identify and mitigate risks. For example, the NIST AI RMF addresses AI-related security vulnerabilities, such as bias and fairness, essential for maintaining trust in AI-integrated systems. Similarly, the ISO/IEC 23894 standard helps organizations create a governance structure that emphasizes accountability, transparency and security–key components for building a resilient, patient-centric healthcare environment.
Adopting Risk Management Frameworks for Cybersecurity Resilience
Risk frameworks such as the OWASP AI framework and ISO 42001 are particularly relevant as healthcare organizations move towards AI-integrated, interoperable health IT environments. OWASP offers tools to manage vulnerabilities within AI systems specifically, providing healthcare organizations with a structured approach to AI security risks. Meanwhile, ISO 42001 promotes a holistic approach to information security management across all operations, not limited to AI, and thus serves as a foundation for comprehensive cybersecurity across a health system.
To fully benefit from these frameworks, healthcare organizations must adopt them at every stage of AI integration, from selection to deployment. This continuous application of risk assessments and security measures ensures that patient data remains protected and aligns with federal goals to empower patients through safe, secure data accessibility.
Cybersecurity Strategies for Clinical AI
As clinical AI systems continue to evolve, so too must the approach to managing the risks associated with their integration. AI’s dependence on data introduces both substantial rewards and significant risks. For instance, a robust enterprise-wide AI platform can offer consolidated security monitoring and data integration, reducing the complexity of managing multiple AI vendors with disparate security protocols. This approach not only enhances security, but aids in data lifecycle management–a key requirement for maintaining compliance with regulations such as HIPAA and GDPR.
However, technology alone is not enough. A comprehensive governance strategy must include strict data management protocols, regular audits and ongoing risk assessments to minimize AI-specific risks. Proactive engagement with AI partners is essential, and it begins with asking the right questions:
- What are their security certifications?
- Have they experienced data breaches, and how were they handled?
- Do they have an incident response plan?
Partnering with AI vendors who prioritize cybersecurity ensures that sensitive patient data remains secure, maintaining patient trust and organizational compliance.
A Federally Aligned Future for Secure, Accessible Healthcare Data
As healthcare embraces AI and the digital transformation, the Federal Health IT Strategic Plan emphasizes the critical balance between data accessibility and security. By strengthening the security and portability of EHI through APIs and interoperable health IT, the federal strategy aims to build a system where patients are empowered to manage their health with confidence that their data is safe, accessible and managed across platforms.
A multi-layered cybersecurity approach, incorporating well-established risk frameworks such as NIST, ISO and OWASP, supports these goals by addressing emerging threats and ensuring that new technologies, like clinical AI, align with ethical and practical safety standards. This framework empowers healthcare systems to deliver secure and innovative care, bridging the gap between operational needs and patient expectations. As healthcare continues its digital transformation, this alignment between federal policy and proactive cybersecurity practices is essential for delivering resilient, accessible and trustworthy patient care in the years ahead.
