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Data Quality Has Huge Implications - Just Ask Regeneron

Posted by Jack Bilson on Jan 29, 2016

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Regeneron stock lost some of its upward momentum earlier this month when incorrect data in the Food and Drug Administration’s Adverse Event Reporting System(FAERS) Database mistakenly showed that their new cholesterol drug, Praluent, might be causing some patient suicides. This resulted in investors pulling away from the high flying stock. Mistakes in FAERS are not new, and in this case the database was wrong. The issue was, in fact, a single case which was just repeated several times in the data. Distractors of FAERS also frequently remind us that not all events are captured, and investigation of reported events sometimes nullifies or changes them at a later date. Is there value in the data? Yes, but the limitations of this data should be understood before action is taken.

Another example of data quality implications is the much debated Sunshine Act, where transparency of Physician compensation by the pharma industry takes precedent. However, many physicians and their medical associations have ,and continue to find, huge gaps and errors in the data that can lead to substantial misunderstandings. Some of these errors have vastly misrepresented actual payments, and may even call into question pharma agreements or policies. At times, they lead us to believe that a doctor has been 'bought' by pharma when in fact they never received money directly.

Embracing the limitations of data and optimizing data inputs is critical when making decisions in healthcare, be those business decisions or clinical ones.

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(image via Synergic Partners)

Topics: Data & Analytics, Provider

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