Use of laboratory data for illicit drug use surveillance and identification of socioeconomic risk factors

Research output: Contribution to journalArticlepeer-review

Abstract

Background: Drug overdose is the leading cause of death among people 25–44 years of age in the United States. Existing drug surveillance methods are important for prevention and directing treatment, but are limited by delayed reporting and lack of geographic granularity. Methods: Laboratory urine drug screen and complete metabolic panel data from patients presenting to the emergency department was used to observe long-term and short-term temporal and geospatial changes at the zip code-level in St. Louis. Multivariate linear regression was performed to investigate associations between zip code-level socioeconomic factors and drug screening positivity rates. Results: An increase in the fentanyl positive drug screens was seen during the initial COVID-19 shutdown period in the spring of 2020. A decrease in cocaine positivity was seen in the fall and winter of 2020, with a return to baseline coinciding with the second major COVID-19 shutdown in the summer of 2021. These changes appeared to be independent of changes in emergency department utilization as measured by complete metabolic panels ordered. Significant short-term changes in fentanyl and cocaine positivity rates between specific time periods were able to be localized to individual zip codes. Zip code-level multivariate analysis demonstrated independent associations between socioeconomic/demographic factors and fentanyl/cocaine positivity rates as determined by laboratory drug screening data. Conclusions: Analyzing clinical laboratory drug screening data can enable a more temporally and geographically granular view of population-level drug use surveillance. Additionally, laboratory data can be utilized to find population-level socioeconomic associations with illicit drug use, presenting a potential avenue for the use of this data to guide public health and healthcare policy decisions.

Original languageEnglish
Article number109499
JournalDrug and Alcohol Dependence
Volume236
DOIs
StatePublished - Jul 1 2022

Keywords

  • Big Data
  • Illicit drug use
  • Laboratory surveillance

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