The opioid crisis in the United States has had devastating effects on communities across the country, leading many states to pass legislation that limits the prescription of opioid medications to reduce the number of overdose deaths. This study investigates the impact of opioid prescription limit laws, which aim to reduce opioid overdose deaths, on opioid prescription rates. An Interrupted Time Series (ITS) model was utilized to assess the policy impact using SAS Viya. The Automatic Time Series Modeling (ATSM) package of SAS® Visual Forecasting software (Viya 4 – Cadence version 2022.12) was used to find the best ARIMA models for each series. The intervention effect on the response variable was analyzed by adding event inputs in the shape of level-shift, ramp and inverse trend to the final ARIMA model for each series through the interactive modeling node of SAS Visual Forecasting. While the policy effectively reduced opioid prescription volumes overall, we observed an unintended consequence. Prescription volume increased in areas where prescribers were located far from patients, highlighting the limitations of state-level policies on doctors.
