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Epidemiological study of opioid use disorder in French emergency departments, 2010-2018 from OSCOUR database
Yves Gallien1,2, Adrien Martin3, Céline Caserio-Schönemann3
1Data Science Division, Santé publique France, Saint-Maurice, France yves.gallien@gmail.com.
Objectives:
Opioid consumption in France has remained stable over the last 15 years, with much lower levels than in the USA. However, few data are available on patients who consume opioids and their use of the health system. Emergency department (ED) data has never been used as a source to investigate opioid use disorder (OUD) in France.
Design/Settings/Participants:
We used the OSCOUR national surveillance network, collecting daily ED data from 93% of French ED, to select and describe visits and hospitalisations after an OUD-related ED visit between 2010 and 2018 using International Classification of Diseases, version 10 (ICD10) codes. We described the population of interest and used binomial negative regressions to identify factors significantly associated with OUD such as gender, age, administrative region, year of admission and ICD10 codes. We also analysed the related diagnoses.
Primary Outcome Measure:
Trend in ED visits for an OUD-related ED visit.
Results:
We recorded 34 362 OUD-related visits out of 97 892 863 ED visits (36.1/100 000 visits). OUD-related visits decreased from 39.2/100 000 visits in 2010 to 32.9/100 000 visits in 2018, resulting in an average yearly decrease of 2.1% (95% CI 1.5% to 2.7%) after multivariate analysis. We recorded 15 966 OUD-related hospitalisations out of 20 359 574 hospitalisations after ED visits (78.4/100 000 hospitalisations) with an increase from 74.0/100 000 hospitalisations in 2010 to 81.4/100 000 hospitalisations in 2018. The analysis of related diagnoses demonstrated mostly polydrug abuse in this population.
Conclusions:
While the proportion of OUD visits decreased in the time frame, the hospitalisation proportion increased. The implementation of a nationwide surveillance system for OUD in France using ED visits would provide prompt detection of changes over time.
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