Introduction:

The de-identification service in Azure Health Data Services enables healthcare organizations to de-identify clinical data while retaining its clinical relevance and distribution.

Key Features:

Machine Learning Models: Utilizes state-of-the-art machine learning models to automatically extract, redact, or surrogate.
HIPAA Compliance: Adheres to the Health Insurance Portability and Accountability Act of 1996 (HIPAA) Privacy Rule.
Versatile Data Handling: Works with unstructured text such as clinical notes, transcripts, messages, or clinical trial studies.

Benefits:

Enhanced Privacy: Ensures patient data privacy by removing or replacing PHI with realistic synthetic data.
Clinical Relevance: Maintains the context of the de-identified data by preserving gender and shifting all dates by the same amount.
Efficient Processing: Offers synchronous (“real-time”) or asynchronous (“batch”) API calls for flexible data processing.

Usage:

Ideal for healthcare organizations looking to unlock the power of their data for research, analysis, or sharing while adhering to privacy regulations.

Compliance:

Fully compliant with HIPAA regulations, making it a reliable choice for handling protected health information (PHI). Coverage includes 27 entities, exceeding the HIPAA 18 Protected Health Information (PHI) identifiers.

De-identification service in Azure Health Data Services

durch Microsoft