DPIAs in Healthcare: A Practical Guide

Navigating data privacy in healthcare can be complex, especially with the stringent requirements set by GDPR Article 35. Conducting a Data Protection Impact Assessment (DPIA) is not just a regulatory checkbox—it’s a practical tool for understanding and reducing the risks that come with handling sensitive patient data. If you’re managing health records, running research, or introducing new technologies, a DPIA can help you protect both your organization and your patients.

This guide is designed to demystify the DPIA process in healthcare settings. We’ll walk you through how to identify high-risk processing, choose appropriate mitigation measures like de-identification, assess residual risk, and document your decisions. Every step is rooted in real-world healthcare scenarios and focused on practical, actionable advice.

With increasing scrutiny around data protection and accountability, it’s crucial to get DPIAs right from the start. We’ll highlight the common pitfalls to avoid and show you how to maintain strong records of processing and demonstrate your lawful basis for processing patient data. Let’s make data protection impact assessments a seamless part of your healthcare compliance journey—so you can focus on what matters most: patient care.

Identifying high-risk processing

Identifying high-risk processing is the cornerstone of an effective Data Protection Impact Assessment (DPIA) in healthcare. Under GDPR Article 35, we must pinpoint data processing activities that are “likely to result in a high risk” to individuals’ rights and freedoms. In the healthcare sector, this usually means any operation involving sensitive patient data, new digital tools, or large-scale initiatives.

But what does “high risk” really look like in practice? Let’s break it down with concrete, healthcare-specific examples and practical guidance to help you spot these situations before they become issues:

• Large-scale processing of special category data: Managing electronic health records, lab results, or genomic data for a significant number of patients falls into this category. The volume and sensitivity of the data amplify the potential impact of a breach.
• Systematic monitoring: This could be ongoing surveillance of patients through wearable devices or continuous monitoring in intensive care units. If the data streams are collected and analyzed routinely, they likely count as high risk.
• Profiling and predictive analytics: Using AI or algorithms to assess patient risk scores, predict disease, or recommend treatment plans. The potential for automated decision-making raises concerns for fairness and accuracy.
• Processing data of vulnerable groups: Healthcare often involves minors, the elderly, or those unable to consent. Processing their data requires extra caution and usually triggers a DPIA.
• Merging datasets from multiple sources: Combining health data with other datasets (like social care or insurance information) increases complexity and the risk of unintended identification.
• Use of new technologies: Introducing telemedicine platforms, mobile health apps, or cloud-based storage tools. New systems can introduce unknown vulnerabilities.

How do we confirm that our processing is high risk? Start with a systematic review of your organization’s records of processing. Map out what data you collect, why, how it’s used, and who has access. Look for any activities that:

• Involve special category data (e.g., health, genetic, biometric data)
• Could impact individuals’ privacy or result in discrimination if misused
• Are not covered by an obvious lawful basis under GDPR
• Scale up existing processes or introduce new technologies

Effective identification of high-risk processing is not just about compliance—it’s about accountability. By proactively flagging and investigating these activities, we create a culture of privacy-first thinking. This also gives us the opportunity to design mitigation measures early, such as robust access controls, de-identification techniques, or enhanced transparency for patients.

In summary, identifying high-risk processing is a continuous process. It requires ongoing engagement with clinical teams, IT, legal, and data protection experts. If you ever have doubts, err on the side of caution: conduct a DPIA and document your decision-making. This builds trust, demonstrates compliance, and protects both your patients and your organization’s reputation.

Mitigation measures and controls

Mitigation measures and controls are at the heart of a robust DPIA in healthcare. Once high risks to patient privacy and data security are identified, the next step is to put practical safeguards in place. The goal is clear: minimize risks to an acceptable level, demonstrate compliance with GDPR Article 35, and foster trust among patients and staff.

What exactly do effective mitigation measures look like for healthcare organizations? They go far beyond IT firewalls and involve a holistic approach to data protection. Here are some proven strategies you can implement:

• De-identification and pseudonymization: Direct identifiers—like names or medical record numbers—should be replaced or removed wherever possible. By making data less directly linked to individuals, you drastically reduce the impact of a potential breach. For research projects, this is often a core mitigation strategy, but even routine clinical operations can benefit.
• Access controls and user authentication: Only authorized personnel should be able to access sensitive health data. Use layered access rights, strong passwords, and, where feasible, multi-factor authentication. This ensures that data is only viewed or edited by those who genuinely need it for their work.
• Encryption in transit and at rest: Encrypting data—whether it’s being transmitted between systems or stored on a device—adds a vital layer of protection. Even if data is intercepted or lost, encryption keeps patient details safe from unauthorized eyes.
• Ongoing monitoring and audit trails: Record every access, change, and transfer of personal data. These records of processing are not only a GDPR requirement but also an essential accountability measure. Regularly review logs to detect suspicious activity early.
• Staff training and awareness: No technical control can replace a well-informed team. Regular training ensures staff understand risks, know how to spot phishing attempts, and handle data responsibly. It’s a simple but powerful way to reduce human error—a leading cause of data breaches.
• Data minimization: Collect only what you truly need, keep it only as long as necessary, and securely dispose of it when it’s no longer required. This principle supports both compliance and good clinical practice.
• Lawful basis checks and documentation: Before processing health data, confirm and record your lawful basis—such as patient consent or vital interests. This is a cornerstone of GDPR compliance and should be integrated into your DPIA process.

Each mitigation measure should be tailored to the specific risks identified in your DPIA. For example, if you’re introducing a new telemedicine platform, focus on secure communications and patient authentication. If launching a research initiative, prioritize de-identification and ethical oversight.

Don’t forget to document every decision and control. Comprehensive records of processing activities and mitigation actions are not just for auditors—they help you evaluate what’s working and where you might need to improve. This ongoing review is key to maintaining accountability and staying ahead of new risks as technology and healthcare needs evolve.

By taking thoughtful, proactive mitigation steps, you don’t just meet regulatory expectations—you build a culture of data protection that benefits everyone in your care ecosystem.

Residual risk and approvals

Once you’ve identified and addressed potential risks during the DPIA process, it’s crucial to focus on residual risk and formal approvals. This step ensures that any remaining risks—those that can’t be fully eliminated—are clearly understood, documented, and managed appropriately before moving forward with data processing activities.

Residual risk refers to the level of risk that remains after all feasible mitigation measures have been implemented. In healthcare, where data sensitivity is exceptionally high, it’s rare to reduce risk to zero. For example, even after applying robust de-identification methods and technical safeguards, minimal risks of re-identification or unauthorized access may persist. Recognizing and documenting these risks is a vital part of the DPIA under GDPR Article 35.

Here’s how to handle residual risk and gain necessary approvals:

• Document the Residual Risk: Clearly describe what risks remain after implementing mitigation measures. Be specific—note if risks are due to technological limitations, human error, or external threats. Link these risks to the specific data processing activities in your records of processing.
• Evaluate Acceptability: Assess whether the residual risk is within acceptable limits for your organization and, more importantly, for patient rights and freedoms. If the risk remains high, GDPR requires additional steps.
• Consult Your Data Protection Officer (DPO): Your DPO should review the DPIA findings, focusing on whether mitigation measures are sufficient and the residual risk is justified by a lawful basis for processing.
• Escalate High Risks: If high residual risks cannot be adequately mitigated, you must consult your national Data Protection Authority (DPA) before proceeding. This is a key accountability measure under GDPR Article 35, ensuring external oversight where necessary.
• Obtain Management Approval: Final approval for the data processing activity should come from senior leadership, based on a comprehensive understanding of identified and residual risks. This step demonstrates organizational accountability and commitment to data protection.

Practical tips for healthcare organizations:

• Keep a detailed audit trail in your records of processing to show how risks were identified, mitigated, and what residual risks remain.
• Use clear, non-technical language when describing residual risks and mitigation measures for decision-makers.
• Update your DPIA if new technologies or processing activities are introduced, as this could change the risk profile.

Addressing residual risk isn’t just a formality—it’s a proactive stance that builds trust with patients and regulators alike. By making approvals contingent on a clear understanding of remaining risks, you strengthen your organization’s culture of data protection and demonstrate true accountability under the GDPR.

Evidence and record-keeping

Evidence and record-keeping are at the heart of showing real-world GDPR compliance in healthcare. When we conduct a Data Protection Impact Assessment (DPIA), it’s not enough to simply complete the process—we must also document each step. This isn’t just about ticking boxes; it’s about building a defensible trail that demonstrates how we identified, assessed, and reduced high risk to patients’ data. Regulators, patients, and even our own teams may need to see this evidence, especially if there’s ever a question about privacy practices.

Why record-keeping matters:

• Accountability: Under GDPR Article 5(2), we must be able to prove our compliance—not just claim it. Keeping DPIA records is a tangible way to show this accountability.
• Continuous improvement: DPIAs are living documents. By recording what risks were found and what mitigation measures were implemented, we create a roadmap for future projects and regular reviews.
• Audit readiness: Should the supervisory authority request proof of compliance, comprehensive records of processing activities and DPIAs act as our best defense.

Essential records for DPIAs in healthcare:

• The rationale for the DPIA: Why was it initiated? What lawful basis for processing personal health data is being relied upon? These context details should be stated clearly.
• Description of processing: Document all flows of data, including sources, recipients, storage locations, and use of de-identification or pseudonymization where relevant.
• Risk identification and mitigation: List all the high risks discovered to patient rights and freedoms, plus the mitigation measures applied. Be specific—vague statements won’t satisfy regulators.
• Consultations: Keep records of discussions with Data Protection Officers, IT, clinicians, and—where appropriate—patient representatives. This shows a balanced, inclusive approach to risk assessment.
• Decisions and justifications: Document why particular actions were taken or not taken, especially if you decided a risk was acceptable or that certain mitigation was not feasible.
• Review schedule: DPIAs should be updated when processing changes or new risks emerge. Set out when and how your assessment will be reviewed and by whom.

Practical tips for robust DPIA records:

• Store DPIA documentation securely but make it accessible to those who need it for compliance and operational reasons.
• Link DPIA records with your broader records of processing to create a unified data protection picture.
• Use version control. This helps show the evolution of risk management and accountability over time.

In healthcare, the stakes are high—so is the scrutiny. Reliable evidence and thorough record-keeping don’t just protect us during investigations; they foster trust with patients and partners by showing that we take data protection seriously from assessment to action.

Typical healthcare scenarios

Healthcare organizations handle some of the most sensitive personal data, which places them under constant scrutiny when it comes to data protection and privacy. Let’s walk through a few typical scenarios where a DPIA isn’t just good practice—it’s essential for demonstrating compliance with GDPR Article 35 and for upholding patient trust.

1. Implementation of Electronic Health Records (EHR) Systems

• High risk: Centralizing patient data can increase risks of unauthorized access, data breaches, and loss of confidentiality.
• Mitigation measures: Role-based access controls, regular audit logs, and encryption both at rest and in transit.
• De-identification: Where possible, storing or sharing data in a de-identified format can minimize the impact of potential breaches.
• Lawful basis: Ensure that data processing is based on explicit patient consent or another lawful basis, such as the provision of healthcare services.
• Records of processing: Maintain clear records detailing what data is processed, by whom, and for what purpose.

2. Clinical Research and Trials

• High risk: Large volumes of sensitive health information, often including special category data, are processed and sometimes shared with external partners.
• Mitigation measures: Data minimization, pseudonymization, and robust data sharing agreements.
• Accountability: Document every processing activity, including justification for data collection and sharing, and regularly review DPIAs as research protocols evolve.
• De-identification: Prioritize de-identified or anonymized datasets for research wherever feasible.

3. Introducing Telemedicine Services

• High risk: Real-time data transmission, video consultations, and remote monitoring can expose patient data to interception or unauthorized access.
• Mitigation measures: Secure video platforms, end-to-end encryption, and multi-factor authentication for both patients and clinicians.
• Lawful basis: Clearly communicate to patients how their data will be used and obtain valid consent where required.
• Records of processing: Keep detailed logs of all telemedicine sessions and data flows, including third-party service providers.

4. Sharing Data with Insurers or Government Agencies

• High risk: Data shared outside the organization can increase the risk of misuse, unauthorized disclosure, or inadequate security controls by third parties.
• Mitigation measures: Data sharing agreements, strict access controls, and regular due diligence on data recipients.
• De-identification: Share only the minimum necessary data, and de-identify wherever possible to protect patient identities.
• Accountability: Ensure all data sharing is recorded and justified, demonstrating compliance with GDPR transparency and accountability principles.

5. Using AI or Automated Decision-Making in Diagnosis

• High risk: Automated processing may impact patient rights or result in significant decisions without human involvement.
• Mitigation measures: Provide human oversight, explain decision-making logic to patients, and regularly assess algorithmic biases.
• Lawful basis: Obtain consent or document another clear legal justification for using AI in clinical decision-making.
• Records of processing: Maintain a transparent record of how AI systems process patient data and the safeguards in place.

In each scenario, a DPIA is your roadmap for identifying high-risk activities, applying mitigation measures like de-identification, ensuring a lawful basis for processing, and keeping thorough records. By embedding DPIAs into your operational workflows, you reinforce your organization’s accountability and commitment to patient privacy under GDPR.

Common mistakes to avoid

Even the most well-intentioned healthcare organizations can stumble when conducting a Data Protection Impact Assessment (DPIA). It’s easy to overlook critical steps or fall into common traps—especially when dealing with complex data flows and sensitive patient information. Let’s walk through the most frequent mistakes so you can avoid the pitfalls and build a robust, GDPR-compliant data protection process.

• Starting the DPIA too late. Waiting until after launching a new health technology or data-driven process before conducting a DPIA is a frequent misstep. A DPIA should be integrated at the earliest planning stages. Early assessment enables you to identify potential high risk areas and embed mitigation measures before any data is processed.
• Underestimating what qualifies as “high risk.” Some organizations misinterpret GDPR Article 35, thinking only large projects require a DPIA. In reality, any processing involving sensitive health data, new technologies, or large-scale profiling can trigger a data protection impact assessment. When in doubt, err on the side of caution and conduct the assessment.
• Neglecting to document the lawful basis for processing. Failing to clearly articulate your lawful basis for each data processing activity is a serious compliance gap. Always record whether you rely on consent, legal obligation, vital interests, or another basis—this should be explicitly captured in your records of processing.
• Overlooking the importance of de-identification. Many organizations assume that simply removing names from data is enough. Effective de-identification or pseudonymization should be robust, ensuring individuals cannot be re-identified without significant effort. This is a cornerstone mitigation measure, especially in healthcare environments.
• Relying on generic templates without customization. Using off-the-shelf DPIA templates can lead to missing unique risks tied to your specific healthcare context. Every DPIA should be tailored to reflect your actual data flows, purposes, and technologies. Customization demonstrates real accountability and a commitment to meaningful data protection.
• Failing to involve the right stakeholders. A DPIA is not a solo exercise. Excluding IT, clinical, legal, or data protection officers limits insight into risks and mitigation strategies. Involving all relevant voices ensures a well-rounded assessment and more effective controls.
• Ignoring ongoing review and updates. Risks change as technologies and practices evolve. Treating the DPIA as a one-time task can leave you exposed to new threats. Regularly review and update your DPIAs, especially when introducing new data uses or responding to incidents.
• Inadequate documentation. Without detailed documentation, you can’t prove compliance or demonstrate accountability to regulators. Your DPIA should clearly record risks, mitigation measures, de-identification strategies, and the rationale behind each decision.

By being proactive and thorough, healthcare organizations can transform the DPIA process from a compliance headache into a powerful tool for trust, innovation, and patient safety. Avoiding these common mistakes is a major step toward building a privacy-first culture that stands up to scrutiny and protects what matters most—your patients’ data.

In healthcare, the stakes for data privacy are incredibly high. Navigating these challenges with a thorough Data Protection Impact Assessment (DPIA) ensures that patient trust is maintained and legal obligations under GDPR Article 35 are met. By systematically identifying activities that pose a high risk, we can proactively design mitigation measures—such as de-identification and robust security controls—to protect sensitive information.

Remember, a DPIA isn’t just about identifying risk; it’s also about demonstrating your organization’s accountability. Documenting your lawful basis for processing, keeping accurate records of processing, and consulting with your team and stakeholders are all part of building a resilient privacy program. This process helps ensure that every step you take is supported and defensible.

Ultimately, integrating DPIAs into your operations is a powerful way to future-proof your healthcare organization. It builds a culture of transparency and responsibility, showing patients and regulators alike that you take data protection seriously. If you’re not sure where to begin, start small—review your current practices, identify high-risk areas, and commit to ongoing improvement. Each step brings you closer to compliance and, most importantly, better care for those you serve.

FAQs

When is a DPIA mandatory?

A Data Protection Impact Assessment (DPIA) is mandatory under GDPR Article 35 whenever a type of data processing is likely to result in a high risk to the rights and freedoms of individuals. This requirement typically applies when organizations plan to introduce new technologies, process sensitive data at scale, or engage in activities such as profiling, automated decision-making, or large-scale monitoring of public areas.

A DPIA must be conducted before starting the processing operation—especially if the operation involves new purposes or methods that could significantly impact data subjects. Examples include processing biometric information, transferring data outside the EU, or handling data related to vulnerable individuals.

In addition, if mitigation measures like de-identification or strong safeguards are not enough to lower the risk, a DPIA becomes even more crucial. Keeping detailed records of processing activities and demonstrating a lawful basis for data handling are also essential parts of accountability, and a DPIA helps document these efforts.

Ultimately, if you’re ever uncertain whether your planned processing could pose a high risk, it’s best practice to perform a DPIA to ensure full compliance and responsible data stewardship.

Who should lead it?

The Data Protection Officer (DPO) should generally lead the Data Protection Impact Assessment (DPIA) process. Under GDPR Article 35, organizations are required to seek the DPO's advice when carrying out a DPIA, especially when the processing activities are likely to result in a high risk to individuals’ rights and freedoms. The DPO’s expertise ensures that all privacy risks are thoroughly analyzed and that appropriate mitigation measures—such as de-identification techniques and selection of a lawful basis—are considered.

While the DPO should take the lead, it’s essential to involve project managers, IT security staff, and other key stakeholders who understand the specific data processing activities. By collaborating, we can ensure that the records of processing are accurate and that the principle of accountability is upheld throughout the assessment. This team approach helps organizations confidently address privacy risks and maintain compliance with GDPR requirements.

Can we reuse a DPIA?

Reusing a Data Protection Impact Assessment (DPIA) can be a practical approach, but it’s only suitable in specific circumstances. Under GDPR Article 35, a DPIA must be reviewed and updated when there is a change in processing that impacts the risk to individuals’ rights and freedoms. If the new project or processing activity is nearly identical in terms of high risk factors, mitigation measures, lawful basis, and de-identification techniques, you might be able to use the existing DPIA as a foundation.

However, simply copying a DPIA without a thorough review can undermine accountability and compliance. Each time you consider reusing a DPIA, it’s essential to confirm that the context, technology, scale, and data subjects remain the same. Always ensure that your records of processing are accurate and reflect any new risks or controls. If there are material changes, you should adapt or redo the DPIA to address those differences properly.

In summary, a DPIA can be reused if the risk profile and processing remain unchanged, but regular reassessment is crucial. This ensures that your organization stays compliant and truly protects individuals’ data, demonstrating your commitment to accountability under the GDPR.

How do we document residual risk?

Documenting residual risk is a key step in the Data Protection Impact Assessment (DPIA) process, as required by GDPR Article 35. After identifying high risks and implementing mitigation measures—such as de-identification, data minimization, or technical safeguards—we need to clearly record any risks that remain. These are known as residual risks.

To document residual risk, we describe the nature and likelihood of the remaining risks in the DPIA report, specifying which risks could still impact data subjects’ rights and freedoms despite the measures taken. This includes outlining the lawful basis for processing, detailing which mitigation strategies were applied, and explaining why the remaining risk is considered acceptable or how it will be further monitored.

It’s important to include this information in our records of processing and keep it updated, demonstrating our commitment to accountability under the GDPR. By doing so, we show regulators—and our data subjects—that we’ve taken a responsible and transparent approach to protecting personal data, while recognizing and managing ongoing risks.