Thomas Falasca, physician and author of Physician’s Guide to Better Medical Decision Making: Critical Thinking in Medicine
The appeal of “real world” evidence is, compelling. First, “real world” evidence (RWE) avoids the high, and rising, cost of randomized controlled trials (RCTs). Second, RWE avoids the concern that evidence from RCTs might be incompletely applicable to the real world, since conditions in the real world inadequately imitate the idealized conditions under which RCTs are conducted. Third, some of the data for RWE may already be available. Fourth, previously unnoticed correlations revealed in big data, might suggest further scientific hypotheses.
However, RWE entails significant concerns. Data set size and data processing speed, may not correct for data inadequacies. In fact, increased processing speed and larger data size may produce errors faster and with greater apparent authority.
Certainly, incomplete data, edited data, suppressed data, multiply counted data, and agenda-directed data are still a problem. Existing data may not be a gift, as it may have been edited or agenda-directed and thus depart from the desideratum of random collection.
A couple of options for detecting unreliability in data suggest themselves, but these also have problems. The first option involves examining the data’s sources. However, the sources might not always be evident, either innocently or by deliberate obfuscation. The second option involves examining the data itself to detect departures from random selection. However, there are significant problems identifying lack of randomness (Falasca, 2019. Physician’s Guide to Better Medical Decision Making: Critical Thinking in Medicine.)
Certainly, “real world” evidence has undeniable appeal. However, there are associated problems that require intense examination.