De-identification of Unstructured Data
De-identifying Unstructured Data to Enable Health Analytics
According to one organization, 80 percent of medical record data will be unstructured within the next two years. Unstructured data can be a critical source of new insights, innovation and knowledge for research hospitals and organizations, medical device companies, insurance companies and medical claims processors, among others. It is possible to share text, PDF, Word or XML data – but a solid strategy built on mitigating risk needs to be developed. This white paper outlines considerations for leveraging this type of data, and outlines the best approach to setting up a risk-based method for de-identification.
“Without this technology a lot of research we want to do would grind to a halt.”
– Dr. Mark Walker, Scientific Director and Co-director of the BORN Registry
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