Reexamining the Evidence Behind Evidence-Based Medicine, Part 2

In part one, we discussed the shortcomings of evidence-based medicine and the disconnect between RCTs and bedside clinical care. Part 2 explores possible solutions, including machine learning-based algorithms.

By Paul Cerrato, MA, senior research analyst and communications specialist, Mayo Clinic Platform, and John Halamka, M.D., Diercks President, Mayo Clinic Platform

To understand the potential contribution of machine learning in evidence-based medicine, it helps to take a closer look at what evidence grading systems like GRADE attempt to accomplish. Typically, they summarize the best evidence on a clinical question, relying heavily on systematic reviews. However, evaluating a body of evidence poses a unique set of challenges. Analysts must examine each study for design limitations, sample size, and various types...