Anonymization in the context of the European Health Data Space

In today's data-driven world, the capture of medical and life science data for research purposes has become increasingly critical. While this data can enhance treatment outcomes, clinical evaluations, product development, and post-market surveillance, strict regulations on data sharing make it difficult to balance the needs of those in need while protecting individual privacy. The global healthcare data monetization market is expected to reach a value of $0.9 billion by 2028, growing at a Compound Annual Growth Rate (CAGR) of 18.5% during forecast period.¹ With the EU health data space becoming a reality, the efficient management of anonymized health data will become increasingly crucial.  

To ensure individual privacy personal health data is only to be used and shared with individual patient consent. Moreover, regulations stipulate that the data cannot be repurposed for scenarios beyond its original intent, such as studies or AI training.

Anonymization is often used to process healthcare data without patient consent, which protects patient privacy. However, this process can also needlessly modify the original dataset, resulting in the loss of statistical properties and information. Using non-accurate data for the training of machine learning algorithms can also introduce bias and ultimately compromise patient outcomes.

In addition, the availability of anonymized healthcare datasets remains limited despite the growing need for more data. As the demand for data increases, the availability of open healthcare datasets struggles to keep up. Consequently, purchasing healthcare data is often prohibitively expensive. Moreover, the healthcare data market may not have an adequate amount of the required data for the intended purpose.

Graceful anonymization outperforms static anonymization in terms of actual utility at the same level of privacy.

Our ZEISS Digital Innovation Anonymization technology provides medical and life science technology companies access to all existing datasets processed by their products – whether on-premise or in the cloud – whether own or third-party data. By utilizing our anonymization solution, both – existing and future datasets can be utilized for research or reselling purposes.

• The graceful anonymization algorithm ensures utility-preserving anonymization, providing high quality data while maintaining the accuracy of the original dataset and ensuring patient privacy.
• The solution is designed to meet regulatory standards and to be compliant with General Data Protection Regulation (GDPR) and Health Insurance Portability and Accountability Act (HIPAA). Thus, customers can be assured that they are complying with regulatory obligations when utilizing or exchanging data for the purposes of research or product design and development.

Our team of experts is ready to help you unlock the power of healthcare data and integrate our anonymization technology in your application. The anonymization solution is independent of the current messaging or data standards you are utilizing and among others works with DICOM, FHIR and HL7 data.