Individual and county-level variation in outcomes following non-fatal opioid-involved overdose

Bibliographic Data

ID11178013
AuthorsEvan Marie Lowder (0000-0002-5855-2479, Criminology, Law and Society, George Mason University, Fairfax, Virginia, USA, corresponding author), Joseph Amlung (0000-0001-6290-6535, Regenstrief Institute, Indianapolis, Indiana, USA), B Ray (0000-0003-3643-775X, Wayne State University), Bradley R Ray (Wayne State University)
Year2020
Volume74
Issue4
Pages369-376
Publication date2020-04-01
Peer ReviewedYes
Open AccessYes
TypeARTICLE
VenueJournal of Epidemiology and Community Health (JOURNAL)
Journal identifiersISSN: 0143-005X • E-ISSN: 1470-2738
PublisherBMJ (PUBLISHER • GB)
DOI10.1136/jech-2019-212915
PMID31919146
OpenAlexW3000133335
LanguageEN
Citations received7
References cited35

BACKGROUND: A lack of large-scale, individually linked data often has impeded efforts to disentangle individual-level variability in outcomes from area-level variability in studies of many diseases and conditions. This study investigated individual and county-level variability in outcomes following non-fatal overdose in a state-wide cohort of opioid overdose patients. METHODS: Participants were 24 031 patients treated by emergency medical services or an emergency department for opioid-involved overdose in Indiana between 2014 and 2017. Outcomes included repeat non-fatal overdose, fatal overdose and death. County-level predictors included sociodemographic, socioeconomic and treatment availability indicators. Individual-level predictors included age, race, sex and repeat non-fatal opioid-involved overdose. Multilevel models examined outcomes following non-fatal overdose as a function of patient and county characteristics. RESULTS: 10.9% (n=2612) of patients had a repeat non-fatal overdose, 2.4% (n=580) died of drug overdose and 9.2% (n=2217) died overall. Patients with a repeat overdose were over three times more likely to die of drug-related causes (OR=3.68, 99.9% CI 2.62 to 5.17, p<0.001). County-level effects were limited primarily to treatment availability indicators. Higher rates of buprenorphine treatment providers were associated with lower rates of mortality (OR=0.82, 95% CI 0.68 to 0.97, p=0.024), but the opposite trend was found for naltrexone treatment providers (OR=1.20, 95% CI 1.03 to 1.39, p=0.021). Cross-level interactions showed higher rates of Black deaths relative to White deaths in counties with high rates of naltrexone providers (OR=1.73, 95% CI 1.09 to 2.73, p=0.019). CONCLUSION: Although patient-level differences account for most variability in opioid-related outcomes, treatment availability may contribute to county-level differences, necessitating multifaceted approaches for the treatment and prevention of opioid abuse

(+)-Naloxone · Buprenorphine · Cohort · Cohort study · Drug · Drug overdose · Emergency department · Environmental health · Heroin · Injury prevention · Naltrexone · Opioid · Opioid overdose · Poison control · Population · Psychiatry · Socioeconomic status · Demography · Emergency Medicine · HIV, Drug Use, Sexual Risk · Internal Medicine · Medicine · Opioid Use Disorder Treatment · Suicide and Self-Harm Studies

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