Determining clinical significance independently from statistical significance? Implications for practice

Background In science, statistics are universally used for making an inference about a population from sample data. The purpose of statistical inference is to determine if a proposed null hypothesis can be rejected, by comparing the probability of an observation to occur under the null hypothesis (p-value) to a chosen alpha level of confidence. The null hypothesis is rejected if the p-value is smaller than alpha. The current focus on null hypothesis statistical significance testing in published work perpetuates confusion between statistical significance and clinical importance. Clinically, there are shortfalls to relying only on statistical inference.