Medical Privacy Protection Implementation Path
Building a compliant de-identified system with OpenMed requires a three-step implementation:
- entity identification layer: The following models are used in combination:
- OpenMed-NER-PHIPDetect: Recognize PHI information such as name/address
- OpenMed-NER-Anatomy: Description of protection of sensitive anatomical areas
- replacement strategy: Adoption of identification results:
- Generic tag replacement (e.g. [NAME])
- Hash encryption (preservation of data analysis value)
- Generative obfuscation (GPT-like models generate alternative texts)
- verification process: through OpenMed'smodel-discoveryThe tool looks for evaluation models and does the final calibration with models with F1-score > 0.95
Example of implementation: use by a hospitalOpenMed-NER-PHIPDetect-SuperClinical-434M+MD5 hashing scheme, under the premise of maintaining the availability of medical records, PHI leakage incidents reduced by 92%. When dealing with text such as "Ms. Zhang XX lives in Chaoyang District, Beijing", it can be accurately identified and replaced with "[PATIENT] lives in [LOCATION]". ".
This answer comes from the articleOpenMed: an open source platform for free AI models in healthcareThe
May not be reproduced without permission:AI productivity tools " How to automate de-identification processing of clinical record data for HIPAA compliance?
English 
简体中文 
日本語 
Deutsch 
Português do Brasil