Skip to main page content
U.S. flag

An official website of the United States government

Dot gov

The .gov means it’s official.
Federal government websites often end in .gov or .mil. Before sharing sensitive information, make sure you’re on a federal government site.

Https

The site is secure.
The https:// ensures that you are connecting to the official website and that any information you provide is encrypted and transmitted securely.

Access keys NCBI Homepage MyNCBI Homepage Main Content Main Navigation
. 2018 Oct;38(10):977-982.
doi: 10.1007/s40261-018-0679-4.

Identification of Somatic Disorders Related to Psychoactive Drug Use from an Inpatient Database in a French University Hospital

Margaux Lafaurie  1 , Liselotte Pochard  1 , Clémence Lotiron  1 , Laurent Molinier  2   3 , Maryse Lapeyre-Mestre  1   2 , Emilie Jouanjus  4   5
Affiliations

Identification of Somatic Disorders Related to Psychoactive Drug Use from an Inpatient Database in a French University Hospital

Margaux Lafaurie et al. Clin Drug Investig. 2018 Oct.

Abstract

Background and objective: Studies have explored hospital records to identify serious complications related to use of psychoactive drugs, but this approach is time consuming with a high rate of false positives. We propose a method to improve the detection of these somatic complications from an inpatient database.

Methods: Hospitalisations in Toulouse University Hospital (France) between 1 July and 31 December 2013 with at least one International Classification of Diseases, Tenth Edition (ICD-10) code related to possible abuse/addiction (F11-F19: "mental and behavioural disorder due to psychoactive substance use", T40-T43: "poisoning", or X61-X62: "self-poisoning") and at least another ICD-10 code unrelated to abuse/addiction were extracted. Hospital discharge summaries (HDS) were reviewed using two strategies: in Strategy 1, all HDS were reviewed, whereas in Strategy 2, associated ICD-10 codes unrelated to abuse/addiction were firstly assessed to preselect some HDS. Positive predictive values (PPVs) were calculated to evaluate their performance.

Results: With Strategy 1, we found 58 psychoactive drug-related somatic complications among the 578 hospitalisations extracted (PPV = 10.0%), including three cases spontaneously reported to the French Addictovigilance Network. Strategy 2 retained 94.8% of the hospitalisations identified with Strategy 1, while the number of reviewed HDS was reduced by half (PPV = 20.1%). Cannabis (56.9%), cocaine (27.6%) and prescription opioids (22.4%) were mainly involved. Complications mainly corresponded to nervous (25.9%) and respiratory and circulatory (22.4%) system disorders.

Conclusions: Combining extraction of ICD-10 codes and a focused review of a preselection of relevant hospitalisations appears to be efficient and time-saving. This method should be applied in other hospital settings before considering the exploration of inpatient data on a wider scale.

PubMed Disclaimer

Similar articles

See all similar articles

Cited by

References

    1. SAMHDA. Drug Abuse Warning Network (DAWN). https://www.datafiles.samhsa.gov/study-series/drug-abuse-warning-network... . Accessed 9 Jul 2018.
    1. Lapeyre-Mestre M, Dupui M. Drug abuse monitoring: which pharmacoepidemiological resources at the European level? Thérapie. 2015;70:147–65. - DOI - PubMed
    1. CSP. Décret n° 2017-885 du 9 mai 2017 pris en application de l’ordonnance n° 2017-51 du 19 janvier 2017 portant harmonisation des dispositions législatives relatives aux vigilances sanitaires. 2017. https://www.legifrance.gouv.fr/eli/decret/2017/5/9/AFSP1706658D/jo/texte . Accessed 9 Jul 2018.
    1. addictovigilance.fr. http://addictovigilance.fr/ . Accessed 9 Jul 2018.
    1. Jouanjus E, Gibaja V, Kahn J-P, Haramburu F, Daveluy A. Signal identification in addictovigilance: the functioning of the French system. Thérapie. 2015;70:113–31. - DOI - PubMed

Substances

LinkOut - more resources