2 methods to de-identify large patient datasets greatly reduced risk of re-identification

Two de-identification methods, k-anonymization and adding a ‘fuzzy factor,’ significantly reduced the risk of re-identification of patients in a dataset of 5 million patient records from a large cervical cancer screening program in Norway.

Read more: 2 methods to de-identify large patient datasets greatly reduced risk of re-identification

Story added 28. July 2017, content source with full text you can find at link above.