De-identification Experts Wanted
Don’t share PHI without reading this
Sharing health information for secondary purposes responsibly has become critical for many providers and healthcare organizations. This is why it is imperative that there is a large pool of de-identification experts who can de-identify that data – or certify that it has already been properly de-identified. These de-identification experts are already in short supply.
Downsides of this shortfall mean that:
- The Safe Harbor de-identification method will be used more frequently. As previous blog posts have indicated, Safe Harbor is just not enough to ensure privacy is maintained. It also tends to destroy the quality of the data, negating the reason it was de-identified in the first place.
- Opportunity for analytics on health data will not occur at all, impeding health research, public health, improvements to the health system, the growth of commercial enterprises, and data-centric innovations in the delivery of care.
- Non-experts may be performing the de-identification – increasing the risks to the organization. These risk may be financial, may be legal, and they may be reputational.
Without a sufficient pool of experts who can meet the growing demand for data sharing, a situation is being created that is stifling innovative data uses.
So how do we grow this pool of experts?
We grow this pool by looking at exactly what is required by an expert. By interpreting the HIPAA Privacy Rule regulation, we can define this expertise to consist of three elements:
- The ability to define “very small” re-identification risk in a defensible way,
- The ability to select appropriate metrics and to measure the risk of re- identification, and
- The ability to transform the data to ensure that the measured risk is indeed “very small.”
There is currently no specific university degree in health data de-identification but there are many industry guides and standards being published that help. While software can automate almost all of the de-identification process, you still need a data scientist familiar with the nuances and complexities of de-identification to ensure risk is minimal.
This is why expert knowledge sharing is so key. Join us October 25-26 in Philadelphia. We are holding a 2-day training session on de-identification for clinical trials. This workshop will include discussion around EMA Policy 0070 and document preparation.
- Can you comply your way to greatness?November 21, 2019
- When to Integrate Anonymization of Documents and DataSeptember 26, 2019
- Deep-Diving into Re-identification: Perspectives On An Article In Nature CommunicationsSeptember 26, 2019
- Learning at Scale: Anonymizing Unstructured Data using AI/MLSeptember 26, 2019
- Early Impact of Health Canada’s New GuidelinesJune 21, 2019
- GDPR and The Future of Clinical Trials Data SharingMarch 18, 2019
- Advancing Principled Data Practices in Support of Emerging TechnologiesMarch 15, 2019
- “Zero Risk Does Not Exist”February 7, 2019
- Is Anonymization Possible with Current Technologies?January 9, 2019
- Comparing the benefits of pseudonymisation and anonymisation under the GDPRDecember 20, 2018