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Semantic Queries Expedite MedDRA Terms Selection Thanks to a Dedicated User Interface: A Pilot Study on Five Medical Conditions

机译:专用的用户界面,语义查询可加快MedDRA术语的选择:对五种医疗状况的初步研究

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Background: Searching into the MedDRA terminology is usually limited to a hierarchical search, and/or a string search. Our objective was to compare user performances when using a new kind of user interface enabling semantic queries versus classical methods, and evaluating term selection improvement in MedDRA. Methods: We implemented a forms-based web interface: OntoADR Query Tools (OQT). It relies on OntoADR, a formal resource describing MedDRA terms using SNOMED CT concepts and corresponding semantic relations, enabling terminological reasoning. We then compared time spent on five examples of medical conditions using OQT or the MedDRA web-based browser (MWB), and precision and recall of the term selection. Results: OntoADR Query Tools allows the user to search in MedDRA: One may enter search criteria by selecting one semantic property from a dropdown list and one or more SNOMED CT concepts related to the range of the chosen property. The user is assisted in building his query: he can add criteria and combine them. Then, the interface displays the set of MedDRA terms matching the query. Meanwhile, on average, the time spent on OQT (about 4 min 30 s) is significantly lower (?35%; p & 0.001) than time spent on MWB (about 7 min). The results of the System Usability Scale (SUS) gave a score of 62.19 for OQT (rated as good). We also demonstrated increased precision (+27%; p = 0.01) and recall (+34%; p = 0.02). Computed “performance” (correct terms found per minute) is more than three times better with OQT than with MWB. Discussion: This pilot study establishes the feasibility of our approach based on our initial assumption: performing MedDRA queries on the five selected medical conditions, using terminological reasoning, expedites term selection, and improves search capabilities for pharmacovigilance end users. Evaluation with a larger number of users and medical conditions are required in order to establish if OQT is appropriate for the needs of different user profiles, and to check if conclusions can be extended to other kinds of medical conditions. The application is currently limited by the non-exhaustive coverage of MedDRA by OntoADR, but nevertheless shows good performance which encourages continuing in the same direction.
机译:背景:搜索MedDRA术语通常仅限于分层搜索和/或字符串搜索。我们的目标是比较使用新型用户界面(支持语义查询和传统方法)时的用户性能,并评估MedDRA中术语选择的改进。方法:我们实现了基于表单的Web界面:OntoADR查询工具(OQT)。它依赖于OntoADR,后者是使用SNOMED CT概念和相应语义关系描述MedDRA术语的正式资源,支持术语推理。然后,我们比较了使用OQT或MedDRA基于Web的浏览器(MWB)在五个医疗状况示例上花费的时间,以及术语选择的精确度和召回率。结果:OntoADR查询工具允许用户在MedDRA中进行搜索:一个人可以通过从下拉列表中选择一种语义属性以及与所选属性范围相关的一个或多个SNOMED CT概念来输入搜索条件。帮助用户建立他的查询:他可以添加条件并将其组合。然后,界面显示与查询匹配的MedDRA术语集。同时,平均而言,花费在OQT上的时间(约4分钟30 s)显着低于花费在MWB上的​​时间(约7分钟)(?35%; p <0.001)。系统可用性量表(SUS)的OQT得分为62.19(被评为良好)。我们还证明了提高的准确性(+ 27%; p = 0.01)和召回率(+ 34%; p = 0.02)。 OQT的计算“性能”(每分钟找到正确的术语)比MWB好三倍以上。讨论:这项初步研究基于我们最初的假设确定了我们方法的可行性:使用术语推理对五个选定的医疗状况执行MedDRA查询,加快术语选择,并提高对药物警戒性最终用户的搜索能力。为了确定OQT是否适合不同用户概况的需要,并检查结论是否可以扩展到其他类型的医疗状况,需要进行大量用户和医疗状况的评估。目前,该应用受到OntoADR对MedDRA的非详尽报道的限制,但是仍然显示出良好的性能,鼓励继续朝同一方向发展。

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