Commentary: Statistical significance and clinical significance - A call to consider patient reported outcome measures, effect size, confidence interval and minimal clinically important difference (MCID)

Abstract

In healthcare research an intervention may be statistically significant based on quantitative analysis; however, simultaneously it may be relatively insignificant to the health or quality of life of patients affected by a particular condition or disease being treated by the intervention - thus may be interpreted as having low clinical significance. An understanding of statistics is fundamental for evidence informed healthcare. Patient-reported outcome measures (PROMs) direct patients to evaluate aspects of their own health, including quality of life, disability and function. Data obtained from PROMs can be used to demonstrate the impact of healthcare interventions on these elements of a person's quality of life. To interpret outcome measure data for clinical decision making, a clinician must understand the concepts of statistical significance and clinical significance. This commentary explores the concepts of patient reported outcome measures (PROMs), their statistical and clinical significance, and explores their relationship with a practical example for the clinician. Limitations of research that only reports p-values and the need to consider effect size, confidence intervals, and minimal clinically important difference are also discussed. Together, these concepts can assist the clinician to evaluate whether an intervention may be suitable for their clinical practice.

Keywords: Clinical practice; Evidence based practice; Measurement; Methodology; Outcomes; Statistics.