Interrupted Time Series Power Calculation using DO Loop Simulations

Interrupted time series analysis (ITS) is a statistical method that uses repeated “snap shots” over regular time intervals to evaluate healthcare interventions in settings where randomization is not feasible. This method can be used to evaluate programs aimed at improving patient outcomes in real-world, clinical settings. In practice, the number of patients and the timing of observations are restricted. This paper describes a statistical program, which will help statisticians identify optimal time segments within a fixed population size for an interrupted time series analysis. This program creates simulations using “DO loops” to calculate the power needed to detect changes over time that may be due to the interventions under evaluation. Parameters used in this program are total sample size in each time period, number of time periods, and the rate of the event before and after the intervention. The program gives the user the ability to specify different assumptions about these parameters and to assess the resultant power. The output from the program can help statisticians communicate to stakeholders the optimal evaluation design.