Statistical comparisons between the counterfactual and observed data at different points post interruption can be used to estimate the short‐ and long‐term effects of the interruption. By modeling data from the pre‐interruption period, the underlying secular trend can be established and extrapolated to the post‐interruption period, creating a counterfactual for what would have occurred in the absence of the interruption.
In an ITS study, data on a group of individuals (eg, hospital, country) are collected at multiple time points both before and after the interruption. The ITS design inherently lends itself to a visual display. However, effective and accurate presentation of the data from ITS studies is needed to enable their inclusion in systematic reviews (including meta‐analysis) and to aid interpretation of the results from the review. This makes ITS studies a valuable design for inclusion in systematic reviews intended to inform policy decisions. The interruption could be planned, such as the roll out of a new health policy, or unplanned, such as an unintended environmental exposure.
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