Moving Beyond Correlation in Clinical Practice

A statistical approach termed “causal inference” could revolutionise ways of identifying effective treatments, according to research from Mayo Clinic. Traditional randomized controlled trials can be expensive and unrepresentative of everyday health conditions, and over-reliance on them sees many treatments applied without adequate support. Observational studies can help justify treatments but can also mislead. However, causal inference, which uses mathematical statements, could change this and allow more effective treatments to be identified.