Identifying the Best De-Identification Protocols

Keeping patient data private remains one of the biggest challenges in healthcare. A recently developed algorithm from nference is helping address the problem.John Halamka, M.D., president, Mayo Clinic Platform, and Paul Cerrato, senior research analyst and communications specialist, Mayo Clinic Platform, wrote this article.In the United States, healthcare organizations that manage or store personal health information (PHI) are required by law to keep that data secure and private. Ignoring that law, as spelled out in the HIPAA regulations, has cost several providers and insurers millions of dollars in fines, and serious damage to their reputations. HIPAA offers 2 acceptable ways to keep PHI safe: Certification by a recognized expert and the Safe Harbor approach, which requires organizations to hide 18 identifiers in patient records so that unauthorized users cannot identify patients. At Mayo Clinic, however, we believe we must do more.In partnership with the data analytics firm nference, we have developed ade-identification approach that takes patient privacy to the next level, using a protocol on EHR clinical notes that includes attention-based deep learning models, rule-based methods, and heuristics. Murugadoss et al explain that “rule-based systems use pattern matching rules, regular expressions, and dictionary and public database look-ups to identify PII [personally identifiable information] elements.” The problem with relying solely on such rules is they miss things, ...
Source: Life as a Healthcare CIO - Category: Information Technology Source Type: blogs