Big Data and Pharmacovigilance, Part I

By Dov Fox

So much new data are created every day that 90 percent of all data worldwide has emerged in just the last two years. This information revolution has the potential, argues Bill of Health guest blogger Ryan Abbott, to transform how we develop new drugs, set clinical practices, and finance health care. His interesting new article paints an alluring “vision of a drug regulatory system powered by big data”:

“When the Food and Drug Administration (FDA) approved the cholesterol-lowering drug simvastatin in 1991, it was based on pre-marketing controlled clinical studies that included a total of 2,423 patients. In 2011 alone, just in the United States, almost a hundred million prescriptions were written for the drug. Imagine the impact of being able to analyze data from every one of those patients to evaluate whether simvastatin is safe and effective.”

The surveillance of pharmaceuticals after they’ve gone to market will matter more and more, Abbott argues, as personalized medicines become more difficult – and perhaps less necessary – to regulate before they’re released. He proposes a new plan for the post-market regulatory system that relies on the health information exchanges (HIE) created by the HITECH and Affordable Care Acts. These exchanges are slated to amass a vast repository of data on individual patients. Their large size and inclusive nature will enable more accurate analyses in observational research, Abbott suggests, and in ways that minimize the bias and selectivity problems associated with current data sets.

There are at least three obstacles to the integration of these exchanges in drug regulation. First, HIEs will be expensive. While the federal government provided considerable funding to get these exchanges off the ground, Abbott recognizes that in order to remain viable, they will probably have to sustain themselves financially. Second, their meaningful impact on post-marketing surveillance will require consistent reporting standards and information-sharing mechanisms. Third are important patient concerns about the privacy of their personal health information. States are experimenting with different patient participation models to address privacy concerns. For example, Abbott notes that in some states HIEs are free to exchange information without patient consent, while in others patients can opt-out of information exchange altogether. Either is permitted by HIPAA, so long as the information is de-identified so it can’t be used to identify individual patients.

Abbott argues that it’s worth tackling such concerns that the adoption of HIEs pose for citizens, policy makers, health care providers, and the health care industry, so we don’t squander the opportunity to use health information exchanges to their full benefit. Public support for data collection isn’t enough. That data must be translated into a format that regulators can use—something I’ll address tomorrow in my next post on the subject.

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