Background The medical community continues to seek to understand both the causes and consequences of opioid use disorder (OUD). The recent 2019 public release of the Automation of Reports and Consolidated Orders System (ARCOS) database from the years 2006 to 2012 provides a unique opportunity to analyze a critical period of the opioid epidemic with unprecedented data granularity. Objectives This study aims to use the ARCOS dataset to (1) determine significant contributory variables to opioid overdose death rates, (2) determine significant contributory variables to the relative prescription of buprenorphine and methadone, and (3) evaluate the existence of statistically significant geospatial clusters in buprenorphine and methadone prescription rates. Methods This study utilizes multiple databases, including the Centers for Disease Control and Prevention (CDC) Wide-ranging Online Data for Epidemiologic Research (WONDER), the Drug Enforcement Administration (DEA) prescription drug data, and the United States (US) Census demographics, to examine the relationship between the different treatments of OUD. Linear regressions are used to determine significant contributory factors in overdose rate and the buprenorphine-to-methadone ratio. Geospatial analysis is used to identify geographic clusters in opioid overdoses and treatment patterns. Results Methadone prescriptions, racial demographics, and poverty were found to significantly correspond to opioid overdose death rates (p < 0.05). Buprenorphine prescriptions were not found to be significant (p = 0.20). Opioid overdoses, metro character, racial categorization, and education were found to significantly correspond to the ratio of buprenorphine to methadone prescribed (p < 0.05). Cluster analysis demonstrated different geospatial distributions in the prescriptions of buprenorphine and methadone (p < 0.05). Conclusion Historically, methadone prescriptions have been higher in areas with high overdose rates. Buprenorphine and methadone prescribing patterns have historically demonstrated different geographic trends.

Objective To evaluate the existence of statistically significant clusters of Cesarean section rates at the county level and assess the relationship of such clusters with previously implicated socioeconomic factors. Results County-level obstetrics data was extracted from March of Dimes, originally sourced from National Center for Health Statistics. County-level demographic data were extracted from the US Census Bureau. Access to obstetricians was extracted from National Provider Identifier records. Rural counties were identified using Rural Urban Commuting Area codes developed by the department of agriculture. The dataset was geospatially analyzed using Moran’s I statistic, a metric of local spatial autocorrelation, to identify clusters of increased or decreased Cesarean section rates. The American South, especially the Deep South, is a major cluster of increased Cesarean section rates. As a general but not absolute pattern, the American West and Midwest had lower Cesarean section rates than the Northeast. Focal areas of increased Cesarean section rates included the Kansas-Nebraska border, Michigan’s upper peninsula, and the New York City metropolitan area. The gross geospatial differences were not explained by rurality, obstetric access, or ethnic and racial factors alone.

Prematurity and low birth weight are of concern in neonatal health. In this work, geospatial analysis was performed to identify the existence of statistically significant clusters of prematurity and low birth weight using Moran’s I. Data was obtained from March of Dimes and the National Center for Health Statistics for the years 2015 to 2019. Analysis demonstrated the presence of hotspot (High-High) and coldspot (Low-Low) geographic clusters of these variables in regions across the United States. Additionally, factorial ANOVA was performed, and revealed the significance of demographic variables of interest. Given the strong relationship between these two variables, regions that are hotspots for one variable, but not the other, are of particular interest for further study.