The Impact of Opioid Prescribing Limits on Drug Usage in South Carolina: A Novel Geospatial and Time Series Data Analysis

TL;DR

This study analyzes the effect of South Carolina's 2018 opioid prescribing legislation using a novel geospatial classification and ARIMA time series analysis, revealing overall prescription reductions but increased distant doctor prescribing.

Contribution

Introduces a new classification system based on stakeholder distances and applies ARIMA models to assess policy impact on opioid prescriptions.

Findings

Overall opioid prescriptions decreased after legislation.

Higher prescription volumes in certain geospatial classes.

Increase in distant doctor prescribing suggests doctor shopping.

Abstract

Background: To curb the opioid epidemic, legislation regulating the amount of opioid prescriptions covered by Medicaid (Title XIX of the Social Security Act Medical Assistance Program) came into effect in May 2018 in South Carolina. Methods: We employ a classification system based on distance and disparity between dispensers, prescribers, and patients and conduct an ARIMA analysis on each class and without any class to examine the effect of the legislation on opioid prescriptions, considering secular trends and autocorrelation. The study also compares trends in benzodiazepine prescriptions as a control. Results: The proposed classification system clusters each transaction into 16 groups based on the location of the stakeholders. These categories were found to have different prescription volume levels, with the highest group averaging 96.50 in daily MME (95% CI [63.43, 99.57]) and the lowest 37.78 (95% CI [37.38,38.18]). The ARIMA models show a decrease in overall prescription volume from 53.68 (95% CI [53.33,54.02]) to 51.09 (95% CI [50.74,51.44]) and varying impact across the different classes. Conclusion: Policy was effective in reducing opioid prescription volume overall. However, the volume of prescriptions filled where the prescribing doctor is located more than 1000 miles away from the patient went up, hinting at the possibility of doctor shopping.