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The number needed to treat is an epidemiological measure used in communicating the effectiveness of a health-care intervention, typically a treatment with medication. The NNT is the average number of patients who need to be treated to prevent one additional bad outcome. It is defined as the inverse of the absolute risk reduction, and computed as 1 / {\displaystyle 1/} , where I e {\displaystyle I_{e}} is the incidence in the treated group, and I u {\displaystyle I_{u}} is the incidence in the control group. This calculation implicitly assumes monotonicity, that is, no individual can be harmed by treatment. The modern approach, based on counterfactual conditionals, relaxes this assumption and yields bounds on NNT.
A type of effect size, the NNT was described in 1988 by McMaster University's Laupacis, Sackett and Roberts. The ideal NNT is 1, where everyone improves with treatment and no one improves with control. A higher NNT indicates that treatment is less effective.
NNT is similar to number needed to harm , where NNT usually refers to a therapeutic intervention and NNH to a detrimental effect or risk factor.