Industry Perspectives

Learn the essential requirements for maintaining audit trails during PHI disposal to ensure compliance and protect patient privacy.

Machine-learning anomaly detection for EHRs identifies unusual access, limits breach impact, automates response, and helps meet HIPAA audit requirements.

AI-driven threat detection revolutionizes healthcare security by enhancing response times, predicting risks, and reducing workloads for IT teams.

How AI automates SOC 2 evidence collection for healthcare: continuous monitoring, faster audits, lower costs, multi-framework evidence mapping with human oversight.

AI tools are revolutionizing compliance in healthcare, automating processes to reduce errors and enhance patient data security amidst rising regulations.

Explore how AI enhances compliance tracking in healthcare, improving accuracy, timeliness, and scalability while minimizing risks and costs.

AI detects cloud anomalies in healthcare—real-time EHR and IoMT monitoring, hybrid models to cut false positives, and governance to support HIPAA compliance.

Explore the risks and governance strategies for integrating AI in healthcare incident response, ensuring patient safety and data security.

Explore how AI risk scoring is revolutionizing cybersecurity in healthcare, enhancing threat detection, and optimizing resource management.

Surging breaches and tougher HIPAA/EU rules are forcing healthcare to adopt continuous AI security audits, real-time monitoring, stronger vendor oversight, and blockchain.

With 2025 compliance deadlines approaching, healthcare organizations must address the AI governance talent gap to ensure patient safety and data privacy.

Learn essential practices for safeguarding patient data, reducing breaches, and maintaining compliance in healthcare organizations.

Learn how to conduct effective supply chain security audits in healthcare to protect patient data and ensure compliance.

Assess 5G's impact on healthcare security, highlighting vendor risk, IoT vulnerabilities, zero-trust defenses, and the need for continuous monitoring to protect patients.

Five steps to manage third-party cloud audits in healthcare: set scope, choose auditors, align teams, assess risks, and maintain continuous monitoring.

Avoid five common vendor onboarding security errors in healthcare: poor risk classification, checkbox reviews, weak BAAs, uncontrolled integrations, and no ongoing monitoring.

Explore the top challenges in vendor risk scoring for healthcare and discover strategies to enhance data accuracy, compliance, and security.

Compare nine de-identification solutions for clinical text, structured data, and DICOM imaging, with strengths, use cases, and compliance notes.

Avoid common pitfalls in SOC 2 audits to ensure compliance and protect sensitive patient data in healthcare organizations.

Essential questions to vet healthcare AI vendors—covering performance guarantees, PHI protection, liability, governance, security, explainability, and audit readiness.

Practical steps to secure cloud-hosted PHI: MFA, least privilege, segmentation, audit logging, session controls, API security, and vendor oversight.

Guide to creating and managing FDA-compliant SBOMs for medical devices, covering NTIA elements, lifecycle and vulnerability requirements, formats, and submissions.

Apply the STRIDE threat-modeling framework to identify and mitigate Spoofing, Tampering, Disclosure, DoS, Repudiation, and Privilege risks in medical devices.

Embed security into CI/CD to protect PHI: use RBAC/MFA, IaC, SAST/SCA, centralized immutable logs, AES-256/TLS encryption, BAAs, and vendor risk controls.