INSERM, U1099, F-35000, Rennes, France.
Université de Rennes 1, LTSI, F-35000, Rennes, France.
BMC Med Inform Decis Mak. 2018 Oct 19;18(1):86. doi: 10.1186/s12911-018-0667-x.
BACKGROUND: Pharmacovigilance consists in monitoring and preventing the occurrence of adverse drug reactions (ADR). This activity requires the collection and analysis of data from the patient record or any other sources to find clues of a causality link between the drug and the ADR. This can be time-consuming because often patient data are heterogeneous and scattered in several files. To facilitate this task, we developed a timeline prototype to gather and classify patient data according to their chronology. Here, we evaluated its usability and quantified its contribution to routine pharmacovigilance using real ADR cases. METHODS: The timeline prototype was assessed using the biomedical data warehouse eHOP (from entrepôt de données biomédicales de l'HOPital) of the Rennes University Hospital Centre. First, the prototype usability was tested by six experts of the Regional Pharmacovigilance Centre of Rennes. Their experience was assessed with the MORAE software and a System and Usability Scale (SUS) questionnaire. Then, to quantify the timeline contribution to pharmacovigilance routine practice, three of them were asked to investigate possible ADR cases with the "Usual method" (analysis of electronic health record data with the DxCare software) or the "Timeline method". The time to complete the task and the data quality in their reports (using the vigiGrade Completeness score) were recorded and compared between methods. RESULTS: All participants completed their tasks. The usability could be considered almost excellent with an average SUS score of 82.5/100. The time to complete the assessment was comparable between methods (P = 0.38) as well as the average vigiGrade Completeness of the data collected with the two methods (P = 0.49). CONCLUSIONS: The results showed a good general level of usability for the timeline prototype. Conversely, no difference in terms of the time spent on each ADR case and data quality was found compared with the usual method. However, this absence of difference between the timeline and the usual tools that have been in use for several years suggests a potential use in pharmacovigilance especially because the testers asked to continue using the timeline after the evaluation.
背景：药物警戒包括监测和预防药物不良反应（ADR）的发生。这项活动需要从患者记录或任何其他来源收集和分析数据，以寻找药物与 ADR 之间因果关系的线索。这可能很耗时，因为患者数据通常是异构的，分散在多个文件中。为了方便这项任务，我们开发了一个时间线原型，根据患者的时间顺序来收集和分类患者数据。在这里，我们使用真实的 ADR 病例评估了它的可用性，并量化了它对常规药物警戒的贡献。
方法：使用雷恩大学医院中心的生物医学数据仓库 eHOP（entrepôt de données biomédicales de l'HOPital）评估时间线原型。首先，由雷恩地区药物警戒中心的六名专家测试原型的可用性。他们的经验使用 MORAE 软件和系统可用性量表（SUS）问卷进行评估。然后，为了量化时间线对药物警戒常规实践的贡献，其中三人被要求使用“常规方法”（使用 DxCare 软件分析电子健康记录数据）或“时间线方法”来调查可能的 ADR 病例。记录并比较了两种方法完成任务的时间和报告中的数据质量（使用 vigiGrade 完整性评分）。
结果：所有参与者都完成了任务。可用性可被认为几乎是极好的，平均 SUS 得分为 82.5/100。两种方法完成评估的时间相当（P=0.38），两种方法收集的数据的平均 vigiGrade 完整性也相当（P=0.49）。
结论：结果表明，时间线原型具有良好的总体可用性水平。相反，与常规方法相比，在每个 ADR 病例上花费的时间和数据质量方面没有发现差异。然而，时间线与已经使用了数年的常规工具之间没有差异表明，特别是因为评估后测试人员要求继续使用时间线，它在药物警戒中具有潜在的用途。
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