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潜在药物相互作用的最小信息模型。

A Minimal Information Model for Potential Drug-Drug Interactions.

作者信息

Hochheiser Harry, Jing Xia, Garcia Elizabeth A, Ayvaz Serkan, Sahay Ratnesh, Dumontier Michel, Banda Juan M, Beyan Oya, Brochhausen Mathias, Draper Evan, Habiel Sam, Hassanzadeh Oktie, Herrero-Zazo Maria, Hocum Brian, Horn John, LeBaron Brian, Malone Daniel C, Nytrø Øystein, Reese Thomas, Romagnoli Katrina, Schneider Jodi, Zhang Louisa Yu, Boyce Richard D

机构信息

Department of Biomedical Informatics, University of Pittsburgh, Pittsburgh, PA, United States.

Intelligent Systems Program, University of Pittsburgh, Pittsburgh, PA, United States.

出版信息

Front Pharmacol. 2021 Mar 8;11:608068. doi: 10.3389/fphar.2020.608068. eCollection 2020.

Abstract

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.

摘要

尽管药物相互作用相关不良事件对健康有重大影响,但目前尚无用于管理和共享描述药物之间潜在相互作用证据的标准模型。在其他领域,最小信息模型已被用于围绕能够传达有用信息的简单模型达成社区共识。本文报告了一种用于描述潜在药物相互作用的新最小信息模型。万维网联盟医疗保健和生命科学社区组语义网特别工作组让信息专家和药物相互作用专家深入研究近期文献及特定潜在相互作用。确定了一组共识信息项,以及选定潜在药物相互作用(PDDI)的示例描述。开发了用户简档和用例以证明该模型的适用性。确定了十个核心信息项:涉及的药物、临床后果、严重性、操作分类声明、推荐措施、相互作用机制、背景信息/修正因素、疑似药物相互作用的证据、暴露频率以及暴露人群的伤害频率。八项最佳实践建议提出了PDDI知识工件创建者在将药物相互作用证据综合到旨在帮助临床医生的工件中时,如何最好地使用这十个信息项。该模型已被纳入HL7临床决策支持工作组制定的拟议实施指南以及CDS Connect存储库中发布的PDDI中。该模型的完整描述可在https://w3id.org/hclscg/pddi上找到。

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