Making drug trials relevant to individual consumers– use real world data

Nov 24, 2008

The NYTimes has a really interesting article today on real world testing of drugs. How are consumers to be informed today? There are limited head to head trials, and almost all of the data comes from highly selected groups of individuals under conditions that are nearly impossible to replicate in the real world. Ivory tower medicine indeed, giving us the best case scenarios only…but far from the outcome impact for all the spend and utilization occurring in very different ways out in the real world.

Although thousands of medical studies are completed every year, most have relatively limited goals. They often carefully select patients who have few medical problems other than the one under study, making it easier to get one clear result. They may not look at effects over the long term, assuming that if a treatment helps initially, patients will be better off.

But while such studies can help a drug acquire approval or answer a restricted research question, they can leave patients and doctors in a lurch because they may not tell how the new drug or treatment will work once it is tried in real patients with complex problems. Such limited studies, while they can have value, may no longer be enough, particularly when care has become so expensive and real evidence more crucial.

“They are at the heart of why we have trouble making decisions,” said Dr. Scott Ramsey, a professor of medicine at the University of Washington.

Its an interesting question as to which should be the better gold standard in addressing the patient before a physician: randomized clinical trials with non-matching study populations or outcome databases with real world utilization of patients matching her symptoms?

This used to be a hypothetical question and rationale for the quest for the holy EMR (the one to unite them all). However, recent advances in social networking using pools of individual experiences in places like Patients Like Me and Sermo bring tantalizing “wisdom of the crowds” potential in evaluating the effectiveness of various treatments.

As medical tools increasingly help us to personalize and segment populations, it forces a pause in how the delivery of the appropriate data and heuristics will occur. In a world where we ask individuals to make choices, is our ivory tower approach to group statistics relevant to individuals who want the best for them?