The current landscape around health data privacy and the promise of synthetic data in healthcare.
The healthcare system generates approximately a trillion gigabytes of data annually, and this amount is doubling every two years. Therefore, the amount of data created over the next three years is likely to be more than the data created over the past 30 years. The ecosystem around this data is complex and constantly trying to build the infrastructure needed to sustain this growth in data.
Landscape around data privacy in healthcare
As the data universe grows in healthcare, so do the opportunities for insight. There have been big leaps in the technology and techniques available for better data analysis. Increased accessibility, increased data and increased granularity is great for innovation. However, this can lead to nervousness of lawmakers, regulators, privacy experts and individuals whose data is involved in these healthcare systems.
Firms that have traditionally used the safe harbor method of de-identification are now looking toward the use of the Expert Determination method for de-identified data and alternative insights. Safe Harbor has limitations in utility and doesn’t have the same, in-depth consideration of risk that Expert Determination methods do. Companies typically have a cautious approach as the shift to Expert Determination can be a big change to current processes, and education and support is needed along the way.
Guaranteeing patient privacy important now more than ever.
Data is the fuel, the glue and the product of the new healthcare ecosystem. Data connectivity is a driving force behind innovation and healthcare transformation. Unfortunately, as connectivity increases, so does risk. As more data is connected, clearer profiles of individuals’ lives start to be built. If this isn’t done with consideration of an individual’s right to privacy, it could erode trust with stakeholders and also (were things to go wrong) potentially have damaging implications to individuals.
The effective support involves advice, education and validation in relation to disclosure risk. Many assume the interaction starts once data has been de-identified. However, the collaboration often start much earlier than that. For example, at Mirador Analytics, we support the development stages of new products, planning for dataset joins or analytics planning to ensure risk mitigation throughout. Our upfront input on disclosure risk helps rollout go more smoothly and better prepares teams for discussions on re-identification risk with vendors and potential customers. Thinking about privacy first enables the integration of automated solutions that reduce time to delivery and also allows teams more time to think about data utility, allowing us to focus on maximizing relevant granularity in an easier way.
Challenges around data de-identification in healthcare.
Data privacy with synthetic data in health care.
Despite different anonymization methods and human expert contributions, today, no technique can guarantee zero risks. However, synthetic data can help healthcare researchers create relatively risk-free data, and therefore, it has a high potential in the healthcare industry in the future.
The most exciting thing about synthetic technology is its adoption. Synthetic data has the potential to improve existing AI algorithms, where protected health information isn’t needed, to make decisions influencing human lives in the future.
As a data de-identification expert, we are already seeing partners utilize synthetic data types in their organizations. However, how its greater adoption will look will be dependent on technological advances and regulatory changes.
Mirador Analytics has partnered with Syntegra, a synthetic healthcare data generation leader, to consider any residual risk in synthetic data generated from protected health information. We’re hoping that our analysis work will lead to the creation of best practice risk-reducing methods of creating synthetic datasets.
Read the full interview with Jamie Blackport, CEO and Founder here >>
Author: Mirador Analytics & Syntegra