CEIP-Addictovigilance, Service de Pharmacologie Médicale et Clinique, CHU Toulouse, 37 allées Jules Guesde, 31000, Toulouse, France.
UMR1027 Inserm-Université Paul Sabatier Toulouse III, 37 allées Jules Guesde, 31000, Toulouse, France.
Clin Drug Investig. 2018 Oct;38(10):977-982. doi: 10.1007/s40261-018-0679-4.
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.
已有研究通过查阅医院记录来识别与精神活性药物使用相关的严重并发症,但这种方法既耗时,假阳性率又高。我们提出一种从住院患者数据库中提高此类躯体并发症检出率的方法。
提取 2013 年 7 月 1 日至 12 月 31 日期间在图卢兹大学医院(法国)住院且至少有一个与可能滥用/成瘾相关的国际疾病分类第 10 版(ICD-10)代码(F11-F19:“精神和行为障碍与精神活性物质使用有关”,T40-T43:“中毒”或 X61-X62:“自我中毒”)和至少另一个与滥用/成瘾无关的 ICD-10 代码的住院患者。使用两种策略审查住院病历摘要(HDS):策略 1 审查所有 HDS,策略 2 首先评估与滥用/成瘾无关的相关 ICD-10 代码,以预选择部分 HDS。计算阳性预测值(PPV)以评估其性能。
采用策略 1,我们从提取的 578 例住院患者中发现 58 例精神活性药物相关躯体并发症(PPV=10.0%),包括 3 例在法国药物警戒网络中自发报告的病例。策略 2 保留了策略 1 识别的 94.8%的住院患者,同时审查的 HDS 数量减少了一半(PPV=20.1%)。涉及的主要药物包括大麻(56.9%)、可卡因(27.6%)和处方类阿片(22.4%)。并发症主要对应于神经系统(25.9%)和呼吸系统及循环系统(22.4%)障碍。
联合提取 ICD-10 代码和对相关住院患者的预选择进行重点审查似乎是有效和节省时间的。在更广泛地探索住院患者数据之前,这种方法应该在其他医院环境中应用。