Real world evidence (RWE) - Are we (RWE) ready?

Real world evidence is important as it complements data from randomised controlled trials (RCTs). Both have limitations in design, interpretation, and extrapolatability. It is imperative one designs real world studies in the right way, else it can be misleading. An RCT is always considered higher in the evidence ladder and when there is discordance between a real world study and an RCT, it is the latter which is always considered pristine because of the way it is conducted, e.g., randomization, prospective, double-blind, etc. A real world study can also be done prospectively, and propensity score matching can be used to construct comparable cohorts but may not be able to account for certain biases or confounding factors the way an RCT can do. Nevertheless, comparative effectiveness research in the real world is being resorted to, especially for efficiency studies or pharmacoeconomic analyses, and with the advent of machine learning, the electronic healthcare database mining can result in algorithms that help doctors identify clinical characteristics that correlate with optimal response of a patient to a drug/regimen, thus helping him/her select the right patient for the right drug.