The Food and Drug Administration learned an important, yet highly detrimental lesson in the importance of data quality this week. You may have seen reports on the news of the mistake, but when we go deeper than the just the headlines, we see just how impactful this situation is for not just the FDA, but for the data vendor, and more importantly, for organizations researching drug abuse across the country.
FDA Data Quality Issue Overview and Implications
This week, the FDA announced it had found data quality issues associated with crucial information concerning prescription opioids oxymorphone and hydrocodone. The company behind the data that was supplied concerning these prescriptions, Iqvia, moved quickly to address issues that were identified by the FDA. However, it seems that the data issues will have a more expansive impact than just the FDA, which uses opioid-related data from Iqvia to help determine funding for the DEA’s efforts in studying and researching controlled substances.
The data from Iqvia is also used by companies on Wall Street to determine values of companies based on number of subscriptions being issued for medical products. The data errors had erroneously reported higher numbers of prescriptions for oxymorphone and hydrocodone, which may have altered the prices of stocks of companies associated with these drugs. It should be noted that there is no evidence that these issues did, in fact, change stock prices.
This Could Have Been Avoided
Iqvia hasn’t provided much documentation to show how the issues could have been avoided. However, the fact that the FDA found the discrepancies shows that the data provided by the company should have been verifiable by Iqvia prior to sharing the data with the FDA. Certainly, the verification process utilized by the FDA (be it establishing ranges of acceptable timelines, data points, or other validation standards) was available, or should have been available, to Iqvia prior to the certifying the data as valid, accurate, and actionable. According to a statement from the company saying it stands behind its data methodologies, the Commissioner of the FDA has called for the company to hire a third-party data quality firm to analyze the company’s ongoing work.
In one fell swoop, a data quality issue affected federal funding, potentially impacted stock prices of subscription drug companies on Wall Street, and brought plenty of very public scrutiny on a data vendor. If you didn’t think data quality issues had a profound ripple effect on the organizations and industries surrounding them, this example should prove to you otherwise.