Causality in Medicine: Moving Beyond Correlation in Clinical Practice

A growing body of research suggests it ’s time to abandon outdated ideas about how to identify effective medical therapies.Paul Cerrato, senior research analyst and communications specialist, Mayo Clinic Platform, and John Halamka, M.D., president, Mayo Clinic Platform, wrote this article.“Correlation is not causation.” It’s a truism that researchers take for granted, and for good reason. The fact that event A is followed by event B doesn’t mean that A caused B. An observational study of 1,000 adults, for example, that found those taking high doses of vitamin C were less like ly to develop lung cancer doesn’t prove the nutrient protects against the cancer; it’s always possible that a third factor — a confounding variable — was responsible for both A and B. In other words, patients taking lots of vitamin C may be less likely to get lung cancer because they are mor e health conscious than the average person, and therefore more likely to avoid smoking, which in turn reduces their risk of the cancer.As this example illustrates, confounding variables are the possible contributing factors that may mislead us into imagining a cause-and-effect relationship exists when there isn ’t one. It’s the reason interventional trials like the randomized controlled trial (RCT) remain a more reliable way to determine causation than observational studies. But it’s important to point out that in clinical medicine, there are many treatment protocols in use that are not suppor...
Source: Life as a Healthcare CIO - Category: Information Technology Source Type: blogs