Clinical medicine is anything but precise. To practice medicine well, clinicians need to recognize the many influences that can change, for example, a heart that is working well to one that is in failure. Environment, aging, social influences, and the many unknowns surrounding the workings of the mind on the body all shape this transition from health to disease.
Explore this issue:January 2018
In its essence, clinical medicine involves ambiguity, and practitioners are required to manage, and even be comfortable with, a degree of uncertainty when evaluating and treating a patient. And yet, the research on which practitioners rely to provide good information on how to diagnose and treat patients has, for many years, been based on a measurement that has given at least the illusion of certainty. Use of the p-value to signify that a finding is positive, particularly at an arbitrarily set threshold of <0.05, has governed what is considered “significant” and has strongly influenced which data is accepted for publication and how that data is interpreted for clinical decision making.
But all this is changing. Although many clinicians and researchers over the years have questioned our overreliance on the p-value as a measure that provides sufficient information on which to base the practice of good clinical medicine, a concerted effort to supplement the p-value with other measures more aptly applied to clinical medicine is rapidly evolving.