Industry Perspectives

How SOC 2 and HIPAA controls overlap and how mapping them cuts redundancy 30-40%, speeds audits, and strengthens healthcare data protection.

Learn best practices for SOC 2 risk monitoring in healthcare, focusing on compliance, documentation, team roles, and automation tools.

Explore essential SOC 2 reporting insights for healthcare vendors, focusing on compliance, audit processes, and data protection best practices.

Learn essential steps for SOC 2 PHI monitoring to protect patient data, ensure compliance, and strengthen security in healthcare organizations.

SOC 2 guidance for healthcare supply vendors on protecting PHI, ensuring uptime, managing subcontractors, and maintaining continuous compliance.

Learn how SOC 2 Availability criteria ensure reliable healthcare IT systems, addressing challenges like downtime and data protection.

How SBOMs speed vulnerability detection, improve supply-chain visibility, and help meet FDA cybersecurity rules for medical devices.

Rochester Regional Health received a $15M New York grant to boost cybersecurity and expand telehealth.

Prioritize audits on vendors handling PHI and critical systems to secure patient data and streamline compliance.

AI is reshaping healthcare risk management by predicting patient safety issues, detecting cyber threats, monitoring vendors in real time, and strengthening enterprise governance. This guide explains the opportunities, hidden risks, and practical frameworks—plus how tools like Censinet RiskOps™ modernize ERM with automation and continuous monitoring.

Optimize your risk register to enhance cybersecurity in healthcare by assessing risks based on cost, impact, and likelihood.

AI failures in healthcare create hidden financial, operational, and patient-safety costs—preventable with real-world testing, monitoring, and vendor accountability.

Practical RBAC guidance for healthcare: define clear roles, enforce least privilege and separation of duties, add context-aware policies, automate IAM provisioning, and audit regularly.

How healthcare organizations can secure medical AI with secure-by-design architectures, governance, vendor oversight, MLOps monitoring, and supply-chain risk management.

Healthcare must redesign workflows to harness AI—eliminate data silos, automate admin tasks, and secure systems to improve care and reduce clinician burden.

Practical overview of de-identification, differential privacy, federated learning, and governance for secure, multi-institutional healthcare research.

Discover strategies for prioritizing vulnerabilities in cloud-native environments, reducing noise, and preventing burnout through actionable solutions.

AI predictive models identify cyber, supply chain, vendor, and operational risks in healthcare to prevent breaches, ensure compliance, and protect patients.

Explore critical vulnerabilities in the pharmaceutical supply chain and learn how lessons from this sector can enhance risk management across industries.

Compare penetration testing and vulnerability scanning for healthcare: when to use each, their frequency, operational impact, and how they protect PHI.

Third-party vendors pose hidden risks to patient safety in healthcare. Learn how to manage these challenges effectively.

Practical guidance on building AI governance, reducing bias, ensuring transparency, privacy, and continuous monitoring to keep clinical AI safe and equitable.

Cloud outages threaten patient care in healthcare systems, revealing the urgent need for effective continuity planning and risk assessment.

Practical guide to build and enforce PHI retention policies for HIPAA and state compliance, secure storage, automated retention, and secure destruction.