HIPAA Compliance and Private AI

Private AI’s industry-leading technology identifies and protects patient data within EHRs, clinician’s notes, transcripts, and more for HIPAA-compliant data that machine learning and data science teams can safely utilize.

Protecting Healthcare Data under HIPAA's Safe Harbor

In healthcare, mismanaged data can result in massive fines and long-lasting damage to a company’s reputation. One way to mitigate fines and protect your institution’s reputation is to comply with the Health Insurance Portability and Accountability Act’s (HIPAA) Safe Harbor rule. 

If you comply with the Safe Harbor rule, the length of audits is shortened, and fines are lowered in the event of a data breach. Plus a layer of protection is added to the data you are keeping.

Automatically De-Identify Data Accurate Enough To Meet HIPAA Expert Determination Requirements

The Health Insurance Portability and Accountability Act (HIPAA) Privacy Rule sets a national standard in the US for the protection of individuals’ medical records and other protected health information (PHI). The HIPAA Privacy Rule allows for health information to be de-identified using two methods: the Safe Harbor method, which requires the removal of certain specified identifiers, and the Expert Determination method, where a qualified expert applies statistical or scientific principles to determine whether the risk is “very low” that the information could be used, alone or in combination with other reasonably available information, by an anticipated recipient to identify an individual.


Private AI can help organizations with both HIPAA Safe Harbor and HIPAA Expert Determination requirements.

How Private AI Can Help with HIPAA Compliance

Private AI identifies and redacts all 18 of these entities with higher than human accuracy and directly on premise, meaning that the healthcare organization’s data never leaves its environment. While building the system, Private AI recognized the need for robustness to optical character recognition (OCR) mistakes, grammar errors, and spelling mistakes. 

Try our text web demo to see Private AI’s redaction capabilities in action:

Looking to redact files? Try the file web demo.

Additional Resources

HIPAA Expert Determination
HIPAA Expert Determination Aided by Private AI
phi
What is Protected Health Information (PHI)? 
HIPAA
HIPAA Compliance & Protecting Healthcare Data with Private AI

Download the Free Report

Request an API Key

Fill out the form below and we’ll send you a free API key for 500 calls (approx. 50k words). No commitment, no credit card required!

Language Packs

Expand the categories below to see which languages are included within each language pack.
Note: English capabilities are automatically included within the Enterprise pricing tier. 

French
Spanish
Portuguese

Arabic
Hebrew
Persian (Farsi)
Swahili

French
German
Italian
Portuguese
Russian
Spanish
Ukrainian
Belarusian
Bulgarian
Catalan
Croatian
Czech
Danish
Dutch
Estonian
Finnish
Greek
Hungarian
Icelandic
Latvian
Lithuanian
Luxembourgish
Polish
Romanian
Slovak
Slovenian
Swedish
Turkish

Hindi
Korean
Tagalog
Bengali
Burmese
Indonesian
Khmer
Japanese
Malay
Moldovan
Norwegian (Bokmål)
Punjabi
Tamil
Thai
Vietnamese
Mandarin (simplified)

Arabic
Belarusian
Bengali
Bulgarian
Burmese
Catalan
Croatian
Czech
Danish
Dutch
Estonian
Finnish
French
German
Greek
Hebrew
Hindi
Hungarian
Icelandic
Indonesian
Italian
Japanese
Khmer
Korean
Latvian
Lithuanian
Luxembourgish
Malay
Mandarin (simplified)
Moldovan
Norwegian (Bokmål)
Persian (Farsi)
Polish
Portuguese
Punjabi
Romanian
Russian
Slovak
Slovenian
Spanish
Swahili
Swedish
Tagalog
Tamil
Thai
Turkish
Ukrainian
Vietnamese

Rappel

Testé sur un ensemble de données composé de données conversationnelles désordonnées contenant des informations de santé sensibles. Téléchargez notre livre blanc pour plus de détails, ainsi que nos performances en termes d’exactitude et de score F1, ou contactez-nous pour obtenir une copie du code d’évaluation.

99.5%+ Accuracy

Number quoted is the number of PII words missed as a fraction of total number of words. Computed on a 268 thousand word internal test dataset, comprising data from over 50 different sources, including web scrapes, emails and ASR transcripts.

Please contact us for a copy of the code used to compute these metrics, try it yourself here, or download our whitepaper.