Evaluation of opioid prescribing habits based on analysis of a state prescription drug monitoring program

Background: The current opioid epidemic is perhaps the greatest public health crisis in the United States. Although multiple factors led to the rise of this epidemic, it is without question associated with the rise in opioid prescribing. Objectives: Better understanding of the opioid prescribing may provide insights into populationlevel trends contributing to this epidemic, and opportunities to decrease the magnitude of opioid overdose-related death. Therefore we assessed trends in opioid prescribing habits based on analysis of the Texas Prescription Drug Monitoring Program (PDMP) and geographic, ethnic, and incomerelated data from the US Census Bureau. Study Design: Multiple linear regression analysis of Texas PDMP and US Census Bureau data were performed to assess for correlations to opioid prescribing based on geographic, ethnic, income, and time-related variables. Setting: All controlled substances prescribed in the state of Texas from April 2015 to May 2018 were analyzed. Methods: We obtained data from the Texas PDMP for all controlled substances from April 2015 to May 2018. We performed multiple linear regression analysis of these data along with US Census Bureau data to assess for correlations based on geographic, ethnic, income, and time-related variables. We hypothesized that there would be substantial variability in opioid prescribing habits based on geographic, ethnic, and economic variables. Results: Approximately 200 million pills of controlled substances were prescribed per month over the studied time frame. Overall, high geographic variability was noted, and this strongly correlated to race and ethnicity. Opioid prescribing increased along with the proportion of white residents within a county, but a similar negative correlation was noted with increasing Hispanic population proportion. This correlation was noted throughout the study period, but up until 2017, lower income levels among higher white population had even higher correlation with increased opioid prescribing. Cumulative opioid prescriptions throughout the state fell beginning in 2017. Limitations: This analysis does not include opioids obtained illicitly or from prescriptions outside the state of Texas. The specificity of geographic data are limited to the county level due to irregular entry of zip code data by prescribing pharmacies. Conclusions: In the state of Texas over the studied time period, there was strong correlation for higher rates of opioid prescribing as white population increased despite overall decreased opioid prescribing starting in 2017. Until 2017, this correlation grew stronger as low-income white population increased.