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专家探索器:一种用于医院数据可视化和药物不良事件规则验证的工具。

The expert explorer: a tool for hospital data visualization and adverse drug event rules validation.

作者信息

Băceanu Adrian, Atasiei Ionuţ, Chazard Emmanuel, Leroy Nicolas

机构信息

Ideea Advertising, Bucharest, Romania.

出版信息

Stud Health Technol Inform. 2009;148:85-94.

PMID:19745238
Abstract

An important part of adverse drug events (ADEs) detection is the validation of the clinical cases and the assessment of the decision rules to detect ADEs. For that purpose, a software called "Expert Explorer" has been designed by Ideea Advertising. Anonymized datasets have been extracted from hospitals into a common repository. The tool has 3 main features. (1) It can display hospital stays in a visual and comprehensive way (diagnoses, drugs, lab results, etc.) using tables and pretty charts. (2) It allows designing and executing dashboards in order to generate knowledge about ADEs. (3) It finally allows uploading decision rules obtained from data mining. Experts can then review the rules, the hospital stays that match the rules, and finally give their advice thanks to specialized forms. Then the rules can be validated, invalidated, or improved (knowledge elicitation phase).

摘要

药物不良事件(ADEs)检测的一个重要部分是对临床病例的验证以及对检测ADEs的决策规则的评估。为此,Ideea Advertising设计了一款名为“专家浏览器”的软件。已将匿名数据集从医院提取到一个公共存储库中。该工具具有3个主要功能。(1)它可以使用表格和精美图表以直观且全面的方式显示住院情况(诊断、药物、实验室结果等)。(2)它允许设计和执行仪表板以生成有关ADEs的知识。(3)它最终允许上传从数据挖掘中获得的决策规则。然后专家可以审查这些规则、与规则匹配的住院情况,并最终通过专门的表格给出他们的建议。然后可以对规则进行验证、无效化或改进(知识引出阶段)。

相似文献

1
The expert explorer: a tool for hospital data visualization and adverse drug event rules validation.专家探索器:一种用于医院数据可视化和药物不良事件规则验证的工具。
Stud Health Technol Inform. 2009;148:85-94.
2
Detection of adverse drug events: proposal of a data model.药物不良事件的检测:一种数据模型的提议
Stud Health Technol Inform. 2009;148:63-74.
3
Data mining to generate adverse drug events detection rules.数据挖掘以生成药物不良事件检测规则。
IEEE Trans Inf Technol Biomed. 2011 Nov;15(6):823-30. doi: 10.1109/TITB.2011.2165727. Epub 2011 Aug 22.
4
The ADE scorecards: a tool for adverse drug event detection in electronic health records.药物不良事件记分卡:一种用于在电子健康记录中检测药物不良事件的工具。
Stud Health Technol Inform. 2011;166:169-79.
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Detection of adverse drug events detection: data aggregation and data mining.药物不良事件检测:数据汇总与数据挖掘。
Stud Health Technol Inform. 2009;148:75-84.
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Data-mining-based detection of adverse drug events.基于数据挖掘的药物不良事件检测。
Stud Health Technol Inform. 2009;150:552-6.
7
Adverse drug events prevention rules: multi-site evaluation of rules from various sources.药物不良事件预防规则:对来自不同来源的规则进行多中心评估。
Stud Health Technol Inform. 2009;148:102-11.
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PSIP: an overview of the results and clinical implications.PSIP:结果与临床意义概述
Stud Health Technol Inform. 2011;166:3-12.
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Design of Adverse Drug Events-Scorecards.药品不良事件记分卡的设计
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Toward automatic detection and prevention of adverse drug events.迈向药物不良事件的自动检测与预防。
Stud Health Technol Inform. 2009;143:30-5.

引用本文的文献

1
Automatic assessment of adverse drug reaction reports with interactive visual exploration.基于交互式视觉探索的自动药物不良反应报告评估。
Sci Rep. 2022 Apr 26;12(1):6777. doi: 10.1038/s41598-022-10887-5.