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Buzzwords like “analytics” and “visualization” have been used in the clinical trial space since the ability to collect massive quantities of clinical trial data became a reality. Everyone wants the instant gratification of real-time trend detection, and software developers have responded in kind by providing a dizzying array of analytics options. How do you make an informed decision about which option is the right fit?
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Having worked in the world of clinical research for 15 years, I can’t help but be baffled by the rampant misuse of the word “de-identified” as it relates to the classification of clinical data sets. In the United States, “the HIPAA Privacy Rule provides federal protections for personal health information [PHI] held by covered entities and gives patients an array of rights with respect to that information.” De-identified health information is not PHI and thus is not protected by HIPAA.
It’s a common misconception that if you remove patients’ names from a set of clinical data, then it becomes de-identified and is no longer governed by HIPAA. However, to make a set of clinical data truly de-identified, you must remove much more than just the patients’ names.