Patient Data Security

Why Health Data (Heart Rate, Height, Weight) is Classified as Sensitive under Saudi PDPL 🇸🇦as well as other privacy regulations. Health data, including biometric measurements like heart rate, height, and weight, is considered sensitive because: ⚪️ Directly linked to an individual’s physical well-being and medical history. ⚪️ Could be misused by employers, insurers, or advertisers (e.g., denying jobs/coverage based on health metrics). ⚪️ Even anonymized, combining height/weight with other data can reveal identities. 🔻Risk Scenario Example🔻 A fitness app collects users’ heart rate and weight to provide health insights. A data breach exposes this information. Risks ▪️Insurance Discrimination: Health insurers could raise premiums for users with high heart rates. ▪️Blackmail: Malicious actors target individuals with "abnormal" health data. ▪️False Medical Profiling: Employers might assume obesity = lower productivity. 🔶Best Practices When Collecting HealthData🔶 🔸Explicit Consent & Transparency** - Clearly state: *"We collect heart rate to customize workouts. Data is encrypted and never sold."* 🔸Anonymize/Aggregate Where possible Store aggregated trends (e.g., "30% of users improved heart health") instead of individual records. 🔸PDPL Compliance: Use de-identification techniques and restrict access to authorized personnel only. 🔸Secure Storage - Encrypt data in transit (SSL) and at rest (AES-256). Avoid third-party cloud storage unless certified. 🔸Right to Delete - Allow users to request permanent data deletion (e.g., PDPL’s "Right of Deletion").

On March 11, hackers wiped data from 200,000 systems at Stryker, a $25B medical giant with 56,000 employees. This wasn't a ransomware attack. It was a geopolitical strike that wiped 50 terabytes of data and shut down manufacturing. If a company of that size is vulnerable, what about a smaller company treating cybersecurity as a checkbox exercise? This is a wake-up call, especially now that the EU’s MDR/IVDR overhaul from late 2025 explicitly mandates cybersecurity as a core safety requirement. For founders and product managers, this means a few urgent truths: 1. Security architecture is a Week 1 decision. The choices you make at the concept stage determine if your product can ever meet standards like IEC 62443-4-1 or OWASP without a complete redesign. 2. Your auditor will ask for a threat model. Failing to document how you mitigate risks (per ISO 14971) creates regulatory debt you cannot ignore. It's the top reason for audit failure. 3. A CE mark isn’t the finish line. Post-market surveillance now includes continuous monitoring for new vulnerabilities. 4. Corporate IT and product security are the same frontline. The Stryker breach showed how an enterprise vulnerability can cascade into supply chain disruption and risk patient safety. Adding security later is rarely possible without starting over. Security has to be baked in from the beginning. Paying the price isn’t just about a failed audit—it’s damage to your reputation, business continuity, and ultimately, patient safety. How seriously do you think the industry is addressing cybersecurity today?

🔐 AI in Medical Devices: Brilliant Potential, Serious Cyber Risks Artificial Intelligence and Machine Learning (AI/ML) have unlocked transformative possibilities in diagnostics, decision support, and personalised care. But with that power comes a growing vulnerability. In June 2025, the #FDA issued new draft guidance that sends a clear message: #Cybersecurity in AI/ML-enabled devices is not an afterthought. It must be integrated across the entire Total Product Lifecycle (TPLC)—from concept to post-market. 📌 Why this matters now • The AI/ML #medicaldevice pipeline is rapidly expanding—including 510(k), De Novo, and PMA submissions. • Many models are cloud-connected and continuously learning—meaning vulnerabilities can evolve alongside the algorithm. • Cyber incidents in healthcare are no longer hypothetical; breaches involving telemetry, imaging processors, and AI model poisoning have already happened. 🧭 The FDA’s expanded cybersecurity lens The new draft guidance shifts the focus from reactive fixes to proactive resilience. It ties cybersecurity obligations to: • Secure product design principles from the earliest stages. • AI-specific threat modelling that considers risks like adversarial attacks and model drift. • Comprehensive SBOMs (Software Bills of Materials) covering all components, dependencies, and libraries. • Rigorous post-market monitoring with clear processes for coordinated vulnerability disclosure. 🔄 Human and supply chain factors are critical Cybersecurity in AI/ML medical devices isn’t just about code—it’s also about: 📍Clinician readiness to detect and respond to anomalies. 📍Secure sourcing and vetting of hardware, frameworks, and third-party components. 📍Preventing counterfeit parts and ensuring traceability across the supply chain. 📅 The lifecycle approach The FDA’s message is clear: security is continuous. From concept feasibility to post-market surveillance, manufacturers must demonstrate that devices can withstand known and emerging AI-specific threats—backed by test results, documentation, and transparent processes. 📊 This infographic breaks down the FDA’s June 2025 Draft Guidance, highlighting key requirements, real-world vulnerabilities, and practical action points for developers, regulatory teams, and cybersecurity specialists. For deeper context on connected device regulations, see my earlier infographic: 1️⃣ Cybersecurity Requirements: https://lnkd.in/dd7Nu-K5 💬 Question for you: As AI/ML becomes more autonomous, how should manufacturers and regulators balance innovation speed with cyber resilience? #FDA #AIinHealthcare #MachineLearning #Cybersecurity #MedicalDevices #FDADraftGuidance #TPLC #AIRegulations #MedTech #SaMD #AIML #CyberResilience

7 security and governance steps I recommend for AI-powered health-tech startups to avoid hacks and fines: 1. Pick a framework -> The Health Insurance Portability and Accountability Act (HIPAA) is non-negotiable if you handle protected health information (PHI). Look at the security, privacy, and data breach notification rule requirements. -> If you want a certification (incl. addressing HIPAA requirements), HITRUST is a good place to start due to origins in healthcare. The AI security certification gives you solid controls for these types of systems. -> If you are looking to cover responsible AI as well as security/privacy, ISO 42001 is a good option. Consider adding HIPAA requirements as additional Annex A controls. 2. Publish policies Longer != better. Use prescriptive statements like "Employees must XYZ." If there are detailed steps, delegate responsibility for creating a procedure to the relevant person. Note that ISO 42001 requires an "AI Policy." 3. Classify data Focus on handling requirements rather than sensitivity. Here are the classifications I use: -> Public: self-explanatory -> Public-Personal Data: still regulated by GDPR/CCPA -> Confidential-Internal: business plans, IP, etc. -> Confidential-External: under NDA with other party -> Confidential-Personal Data: SSNs, addresses, etc. -> Confidential-PHI: regulated by HIPAA, needs BAA 4. Assign owners Every type of data - and system processing it - needs a single accountable person. Assigning names clarifies roles and responsibilities. Never accept "shared accountability." 5. Apply basic internal controls This starts with: -> Asset inventory -> Basic logging and monitoring -> Multi-factor authentication (MFA) -> Vulnerability scanning and patching -> Rate limiting on externally-facing chatbots Focus on the 20% of controls than manage 80% of risk. 6. Manage 3rd party risk This includes both vendors and open source software. Measures include: -> Check terms/conditions (do they train on your data?) -> Software composition analysis (SCA) -> Service level agreements (SLA) 7. Prepare for incidents If your plan to deal with an imminent or actual breach is "start a Slack channel," you're going to have a hard time. At a minimum, determine in advance: -> What starts/ends an incident and who is in charge -> Types of incidents you'll communicate about -> Timelines & methods for disclosure -> Which (if any) authorities to notify -> Root cause analysis procedure TL;DR - here are 7 basic security and governance controls for AI-powered healthcare companies: 1. Pick a framework 2. Publish policies 3. Classify data 4. Assign owners 5. Apply basic controls 6. Manage 3rd party risk 7. Prepare for incidents What else?

🏥🔍Datatilsynet recently reprimanded Norsk Helseinformatikk AS (NHI), the operator of Norway’s largest medical information website, for unlawfully processing sensitive data through the use of the Meta Pixel. The decision follows an in-depth investigation into NHI’s website, which hosts thousands of subpages containing detailed information on a wide range of physical and mental health conditions. 🔹The DPA found that NHI used Meta Pixel across the homepage and various subpages, allowing Meta (Facebook/Instagram) to collect extensive information about user journeys through the website. Data points included the specific health-related subpages visited, IP addresses, browser/device fingerprints, and unique cookie identifiers. The DPA emphasised that even though the website did not directly record a user’s specific health diagnosis or condition, tracking the subpages visited allowed for the inference of a person’s likely health status, such as an interest in articles on epilepsy, depression, or celiac disease. This ability to deduce health status, whether indirect or probabilistic, was central to the DPA’s determination. 🔸NHI argued for a restrictive reading of “sensitive data,” maintaining that visiting a health-related page does not equate to revealing a health condition and that such inferences would be speculative. The DPA, referencing recent CJEU judgments (including C-184/20, C-252/21, and C-21/23), categorically rejected this argument, affirming that the threshold for data to be classified as “sensitive” under Article 9 GDPR is intentionally low. 🔸The fact that a user’s behaviour on a health site can enable the drawing of conclusions about their health—regardless of whether those conclusions are correct or whether other data is cross-referenced—is sufficient for Article 9 to apply. The DPA further clarified that sensitive data protection is not contingent on the controller’s ability to combine data but on the possibility of deduction, especially given the extensive data ecosystem accessible to third parties like Meta. 🔹On the question of consent, the DPA examined NHI’s cookie banner and privacy policy. The banner, implemented through Cookiebot, offered three options—but the “Allow all cookies” button was prominently styled, while the more privacy-protective “Only necessary cookies” button was less noticeable. The DPA found that this design amounted to a “#darkpattern,” subtly nudging users to accept non-essential trackers, thereby undermining the principle of freely given consent. Further, the privacy policy incorrectly stated that no sensitive data would be processed, meaning users could not have given informed consent for tracking and sharing their health-related browsing data. 🔸The decision sets a clear precedent: tracking website visits to subpages containing information about specific medical issues constitutes the processing of special category data under the GDPR. #gdpr #privacy #advertising #cookies #profiling

Protecting Patient Privacy: Why Hospitals in Zambia Must Register Under the Data Protection Act Trust in healthcare begins the moment a patient walks up to the reception desk. At that point, they hand over more than a hospital card. They share names, NRC numbers, contact details, and sensitive medical information. Under Zambia’s Data Protection Act No. 3 of 2021, this information is classified as personal data and sensitive personal data, placing hospitals among the institutions with the highest responsibility to protect patient privacy. Legal Obligations for Healthcare Facilities Hospitals, clinics, and laboratories are required to register with the Office of the Data Protection Commissioner before processing patient information. Personal data includes any information that can identify a patient, while sensitive personal data covers details about health, genetic and biometric data, race or ethnicity, marital status, beliefs, and information relating to children or vulnerable groups. Section 12: Principles for Handling Patient Information Section 12 of the Act sets the standards for how patient data must be managed. Hospitals must process information lawfully, fairly, and transparently. Data collected must serve clear medical or administrative purposes and must be limited to what is necessary for those purposes. Records must be accurate and updated, kept only for as long as necessary, processed in line with patient rights, and protected against unauthorised access or misuse through proper security measures. Even when information is used for research, statistics, or archiving, Section 12 requires that this use remains compatible with the original purpose for which the data was collected. These rules elevate confidentiality from a professional courtesy to a binding legal duty. Section 14: Processing Sensitive Health Data Section 14 recognises that hospitals routinely process highly sensitive information and outlines when this is allowed. Processing may take place when necessary for medical diagnosis, treatment, administration of health services, legal claims, or matters of public interest. Importantly, sensitive data must be handled by or under the supervision of licensed healthcare professionals who are bound by secrecy obligations. This requirement protects the dignity and privacy of every patient, even when information must be shared within the facility or with regulators. Why Registration Builds Trust Registering with the Data Protection Commissioner demonstrates that a hospital values privacy and complies with the law. It reassures patients that their information is safe and handled responsibly. Registration also strengthens accountability, reduces legal risk, and ensures that staff understand their obligations when collecting and managing patient information. #DataProtectionExpert #ZambiaHealthcare #PrivacyLawexpert #HealthDataSecurity #DataProtectionAct #PatientRights #HealthcareCompliance #ZambiaLaw #LegalInsighs

Designers: If your product touches personal health data, your decisions aren’t just UX. They are compliance. In healthcare, we design under HIPAA: a U.S. law that protects PHI (Protected Health Information). PHI is anything that connects a person’s identity to their health: • Name  • Date of Birth • Conditions, meds, test results • Even billing info If exposed to the wrong person? It’s a privacy breach and a HUGE legal issue. Here are 5 things I always build into HIPAA-safe platforms: - Flag PHI fields early - Limit what different roles can see - Require authentication before access - Log who changed what, and when - Communicate consent in plain language I broke each one down in this carousel with examples you can use today. Save it for your next HealthTech project or share it with someone building one!

Tips for Integrating Your Product with U.S. Healthcare Systems When is a health tech product’s development complete? Seems like a simple question, but it evokes a wide range of responses based upon who you ask.  To a start-up product team, they may deem the product to be complete when it meets they’re internal requirements.  To a healthcare system the product is complete when it is able to fully integrate with their EHR, has the necessary security certifications and compliance with regulations like HIPAA and GDPR. The consequences of this disconnect leads to delays in achieving product/market fit and a slower ramp in sales. The good news is that it is a relatively easy mistake to avoid if you have access to the right experts during the product definition phase.   Below are (4) things to think about when building products sold to healthcare systems: 1. User Experience + Clinical Workflow: Keeping the user in mind is key to the adoption and utilization of a new solution. Whether it be hardware or software, if the user interface isn’t intuitive or doesn’t align with the existing clinical workflow, use of the system will fall below expectations. It’s critical to consistently seek feedback from target users during the product development process. 2.⁠ ⁠Data Security and Privacy: Healthcare systems manage, store, and transfer a massive amount of electronic personal health information (ePHI). Data security and privacy to protect ePHI from unauthorized access or breaches is a crucial priority. Vendors must comply with HIPAA regulations and maintain applicable certifications on how they manage ePHI and other sensitive data to show proof of their policies and procedures to healthcare systems. 3.⁠ ⁠Interoperability: Applications and solutions must adhere to standards for Healthcare IT system integrations. Companies should be designing software and hardware with interoperability in mind to allow for integration with health system electronic health record (EHR) software and ancillary systems. 4.⁠ ⁠Regulatory and Compliance Requirements: Vendors developing and deploying solutions must comply with strict requirements in regards to HIPAA, GDPR, and FDA regulations. Before launching a new product to the healthcare industry, developers must adhere to regulatory and compliance requirements that exist to protect sensitive data from being mishandled or shared inappropriately. At The Range we have assembled a vast network of healthcare IT and cybersecurity experts, available to make sure that early stage companies fully understand how to build their product so it seamlessly integrates with their customers existing workflow and systems. To learn more please go to therangeadvisors.com or message me directly.

Given the enormous breaches in 2024, HHS is stepping up their game; shifting many best practices to requirements. Here are 22 takeaways. 1. Make all specifications mandatory, with limited exceptions. 2. Require written policies, procedures, plans, and analyses for Security Rule compliance. 3. Modernize definitions and specifications to align with current technology and terminology. 4. Compliance Timelines: Introduce specific deadlines for meeting requirements. 5. Maintain a technology asset inventory and network map of ePHI movement, updated annually or with environmental changes. 6. Require detailed, written assessments including inventory reviews, threat identification, and risk level evaluation. 7. Notify entities within 24 hours of changes to ePHI access. 8. Written restoration procedures for critical systems within 72 hours. 9. Analysis of system criticality for restoration prioritization. 10. Incident response plans, reporting protocols, and regular testing. 11. Conduct annual audits to ensure Security Rule compliance. 12. Business Associate Verification - Annual verification of technical safeguards by a subject matter expert with written certification. 13. Mandate encryption of ePHI at rest and in transit, with exceptions. 14. Anti-malware, software minimization, and port disabling based on risk analysis. 15. Multi-factor authentication required. 16. Perform vulnerability scans every six months and penetration tests annually. 17. Enforce segmentation to isolate sensitive systems. 18. Require dedicated technical controls for backup and recovery. 20. Test and review security measures annually. 21. Notify covered entities of contingency plan activations within 24 hours. 22. Require plan sponsors to comply with safeguards, ensure agents follow requirements, and notify plans within 24 hours of contingency plan activation. Public comments due in 60 days.

🏥 #Cyber #Hygiene in #Healthcare: European Union Agency for Cybersecurity (ENISA) Practical #Guidance for All #Health #Entities #ENISA has released a hands-on guide to help both large hospitals and small clinics strengthen their cyber hygiene and resilience — a growing necessity in today’s threat landscape. 📌 Key Takeaways: 🔐 Protect critical systems & devices ▫ Regular updates, secure configurations, access control, and backups 🌐 Secure networks & communications ▫ Segment networks, enforce MFA & VPN, deploy email and web filtering 📱 Manage mobile devices & telehealth ▫ Use strong credentials, remote wipe, encryption, and app controls 📁 Keep patient data safe ▫ Encrypt data, classify sensitivity, monitor access, and secure EHR systems 🚨 Be ready for incidents ▫ Have an incident response plan, perform drills, collaborate with peers & CSIRTs 🔗 Secure the #ICT #supplychain ▫ Include cybersecurity in procurement and onboarding/offboarding 🎓 Educate staff at all levels ▫ Role-based training, phishing simulations, awareness campaigns 🏢 Don’t forget physical security ▫ Badge policies, secure devices, audit cameras, and maintain critical infrastructure 📖 A must-read for healthcare providers seeking actionable, scalable practices to prevent cyber threats and safeguard patient care. #ENISA #CyberHygiene #HealthcareCybersecurity #HealthTech #Infosec #Hospitals #Resilience #EHR #CyberAwareness #DigitalHealthSecurity #CyberResilience Tinexta Cyber TINEXTA S.P.A. https://lnkd.in/diuW-BF9