By Travis May
In my earlier post, The Fragmentation of Health Data, I gave an overview of where data comes from and how it flows across the healthcare ecosystem. This post will focus on the landscape of privacy-preserving technology and approaches to protecting privacy during those data flows.
In the US, millions of healthcare events take place every day, ranging from patients undergoing lab tests, to patients picking up prescriptions at a pharmacy, to individuals passing away. There are many analytical and public health uses of this data, including:
- population-level statistics (“How many measles cases are there among 5–10 year olds in California”)
- discovering the effectiveness of treatments (“What is the 10-year survival rate of patients who take a particular drug?”)
- discovering adverse events (“Are cancer rates high among patients who receive a particular medical device?”)
- discovering new targeted therapies