| Autor: |
Margaux, Lafaurie, Liselotte, Pochard, Clémence, Lotiron, Laurent, Molinier, Maryse, Lapeyre-Mestre, Emilie, Jouanjus |
| Rok vydání: |
2018 |
| Předmět: |
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| Zdroj: |
Clinical drug investigation. 38(10) |
| ISSN: |
1179-1918 |
| Popis: |
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.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.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.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. |
| Databáze: |
OpenAIRE |
| Externí odkaz: |
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