Access to Electronic Health Records (EHRs) is strictly regulated. Yet, for a long time, monitoring this access was a paper tiger in many healthcare institutions. Logs were kept on who viewed what, where, and when, but actual enforcement often consisted of incidental manual spot checks. Now, midway through 2026, this reactive approach is fundamentally inadequate. The Dutch Health and Youth Care Inspectorate (IGJ) and the Dutch Data Protection Authority (AP) are enforcing the Supplementary Provisions for the Processing of Personal Data in Healthcare Act (Wabvpz) more strictly than ever.
The impossibility of manual checks
A mid-sized hospital or healthcare facility generates millions of log lines daily. The patient's right to request an electronic logging overview (active since July 2020) and the heightened supervisory frameworks of 2026 place the operational burden squarely on the healthcare provider. According to standards like NEN 7510 and NEN 7513, simply registering system actions is no longer sufficient; there must be demonstrable, structural monitoring for unauthorized access (often referred to as snooping).
Compliance officers manually scanning spreadsheets with millions of log rows are looking for a needle in a haystack. The inevitable result: suspicious patterns—such as an employee unlawfully viewing the medical file of a neighbor, family member, or local celebrity—are structurally missed. This is not due to a lack of effort, but simply a lack of scalability.
Why AI is indispensable for Wabvpz logging requirements
This is exactly where autonomous agent systems transform the role of compliance and security. Within our AI Services, we are seeing an accelerated and successful adoption of our AI agent ZIA within the healthcare sector. Instead of periodic sampling, ZIA continuously analyzes one hundred percent of the logging metadata.
ZIA utilizes advanced pattern recognition without the system ever needing to access the raw, privacy-sensitive medical content of the files. The agent focuses exclusively on metadata and contextual anomalies:
- Is a nurse requesting data from a department where they are not scheduled to work that day or week?
- Are specific files being accessed unusually often outside of regular working hours?
- Is there a surname or postal code match between the healthcare provider and the patient, without a formally registered treatment relationship in the system?
When these types of suspicious "views" occur, ZIA autonomously compiles a clear report in accordance with the applicable NEN 7510 frameworks. The compliance officer receives a substantiated alert with clear context and a risk weighting, rather than an unreadable dump of thousands of data rows.
Operational certainty in 2026
Through the deployment of specific pattern recognition via AI agents, compliance with the Wabvpz is no longer viewed as a heavy administrative burden. Instead, it acts as a catalyst for genuine, proactive information security. The business risks of major data breaches, reputational damage, and hefty administrative fines decrease drastically. Simultaneously, the scarce and valuable time of security and privacy teams is finally spent on targeted investigations and improvements, rather than manual verification work.
Sources
- Health and Youth Care Inspectorate (IGJ): Information Security and NEN 7510
- Overheid.nl: Wabvpz - Supplementary Provisions for the Processing of Personal Data in Healthcare Act
- Dutch Data Protection Authority (AP): IGJ and AP tighten supervision of log files
Would you like to know how ZIA can help your organization automatically, securely, and efficiently meet the strictest logging requirements of the Wabvpz and NEN 7510? Reach out to our experts via contact for a targeted, practical demonstration.