A Minimal Information Model for Potential Drug-Drug Interactions.
A Minimal Information Model for Potential Drug-Drug Interactions.
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DOI：
10.3389/fphar.2020.608068
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发表时间：
2020
影响因子：
5.6
通讯作者：
Boyce RD
中科院分区：
文献类型：
--
作者：
Hochheiser H;Jing X;Garcia EA;Ayvaz S;Sahay R;Dumontier M;Banda JM;Beyan O;Brochhausen M;Draper E;Habiel S;Hassanzadeh O;Herrero-Zazo M;Hocum B;Horn J;LeBaron B;Malone DC;Nytrø Ø;Reese T;Romagnoli K;Schneider J;Zhang LY;Boyce RD
尽管与药物相互作用相关的不良事件对健康有重大影响，但没有标准模型用于管理和共享描述药物之间潜在相互作用的证据。最小信息模型已经在其他社区中使用，以围绕能够传达有用信息的简单模型建立社区共识。本文报道了一种新的最小信息模型来描述潜在的药物相互作用。万维网联盟的医疗保健和生命科学社区组语义网的一个工作组邀请信息学家和药物相互作用专家深入研究最近的文献和特定的潜在相互作用。确定了一组共识信息项，沿着选定潜在药物相互作用（PDDI）的示例描述。开发了用户配置文件和用例，以证明该模型的适用性。确定了10个核心信息项：涉及的药物、临床后果、严重性、操作分类声明、建议的措施、相互作用机制、背景信息/修改因素、疑似药物相互作用的证据、暴露频率和对暴露人员的伤害频率。八个最佳实践建议提出了PDDI知识工件创建者如何在将药物相互作用证据合成为旨在帮助临床医生的工件时最好地使用10个信息项。该模型已被纳入由HL 7临床决策支持工作组制定的拟议实施指南和CDS Connect存储库中发布的PDDI中。该模型的完整描述可以在https://w3id.org/hclscg/pddi上找到。
Despite the significant health impacts of adverse events associated with drug-drug interactions, no standard models exist for managing and sharing evidence describing potential interactions between medications. Minimal information models have been used in other communities to establish community consensus around simple models capable of communicating useful information. This paper reports on a new minimal information model for describing potential drug-drug interactions. A task force of the Semantic Web in Health Care and Life Sciences Community Group of the World-Wide Web consortium engaged informaticians and drug-drug interaction experts in in-depth examination of recent literature and specific potential interactions. A consensus set of information items was identified, along with example descriptions of selected potential drug-drug interactions (PDDIs). User profiles and use cases were developed to demonstrate the applicability of the model. Ten core information items were identified: drugs involved, clinical consequences, seriousness, operational classification statement, recommended action, mechanism of interaction, contextual information/modifying factors, evidence about a suspected drug-drug interaction, frequency of exposure, and frequency of harm to exposed persons. Eight best practice recommendations suggest how PDDI knowledge artifact creators can best use the 10 information items when synthesizing drug interaction evidence into artifacts intended to aid clinicians. This model has been included in a proposed implementation guide developed by the HL7 Clinical Decision Support Workgroup and in PDDIs published in the CDS Connect repository. The complete description of the model can be found at https://w3id.org/hclscg/pddi.
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影响因子：
8
作者：
Daniels, Calvin C.;Burlison, Jonathan D.;Hoffman, James M.
通讯作者：
Hoffman, James M.
影响因子：
1.9
作者：
He, Yongqun;Sarntivijai, Sirarat;Smith, Barry
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Smith, Barry
DOI：
10.1111/j.1365-2710.2005.00676.x
发表时间：
2005-10-01
影响因子：
2
作者：
Chung, L;Chakravarty, EF;Bush, TM
通讯作者：
Bush, TM
影响因子：
--
作者：
Brazma A
通讯作者：
Brazma A
DOI：
10.1093/jamia/ocx010
发表时间：
2017-07-01
影响因子：
6.4
作者：
Fung, Kin Wah;Kapusnik-Uner, Joan;Bodenreider, Olivier
通讯作者：
Bodenreider, Olivier