SMARTSync:迈向以患者为导向的药物和解

Timoteus B. Ziminski, A. D. L. R. Algarin, R. Saripalle, S. Demurjian, E. Jackson
{"title":"SMARTSync:迈向以患者为导向的药物和解","authors":"Timoteus B. Ziminski, A. D. L. R. Algarin, R. Saripalle, S. Demurjian, E. Jackson","doi":"10.1109/BIBMW.2012.6470243","DOIUrl":null,"url":null,"abstract":"Interactions between prescription medications, over-the-counter drugs, and nutritional supplements can have negative consequences for patients. There is a need for the reconciliation across this spectrum spurred on by the adoption of electronic medical records by healthcare providers and the usage of personal health records by patients. In such a setting, unifying information from multiple sources through automated reconciliation can address adverse medication interactions, track adverse medication reactions, and avoid overmedication. This requires mitigating the integration issues of multiple data sources and systems. In this paper, we leverage Harvard University's SMART framework to perform medication reconciliation across different data sources, with the long-term goal of providing robust decision support for overmedication and adverse interactions. Our prototype application SMARTSync provides ontology-backed recognition of interactions, decision support, and is able to warn a patient (or notify a provider) of potential medication problems.","PeriodicalId":6392,"journal":{"name":"2012 IEEE International Conference on Bioinformatics and Biomedicine Workshops","volume":null,"pages":null},"PeriodicalIF":0.0000,"publicationDate":"2012-10-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"9","resultStr":"{\"title\":\"SMARTSync: Towards patient-driven medication reconciliation\",\"authors\":\"Timoteus B. Ziminski, A. D. L. R. Algarin, R. Saripalle, S. Demurjian, E. Jackson\",\"doi\":\"10.1109/BIBMW.2012.6470243\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Interactions between prescription medications, over-the-counter drugs, and nutritional supplements can have negative consequences for patients. There is a need for the reconciliation across this spectrum spurred on by the adoption of electronic medical records by healthcare providers and the usage of personal health records by patients. In such a setting, unifying information from multiple sources through automated reconciliation can address adverse medication interactions, track adverse medication reactions, and avoid overmedication. This requires mitigating the integration issues of multiple data sources and systems. In this paper, we leverage Harvard University's SMART framework to perform medication reconciliation across different data sources, with the long-term goal of providing robust decision support for overmedication and adverse interactions. Our prototype application SMARTSync provides ontology-backed recognition of interactions, decision support, and is able to warn a patient (or notify a provider) of potential medication problems.\",\"PeriodicalId\":6392,\"journal\":{\"name\":\"2012 IEEE International Conference on Bioinformatics and Biomedicine Workshops\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2012-10-04\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"9\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2012 IEEE International Conference on Bioinformatics and Biomedicine Workshops\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/BIBMW.2012.6470243\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2012 IEEE International Conference on Bioinformatics and Biomedicine Workshops","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/BIBMW.2012.6470243","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 9

摘要

处方药、非处方药和营养补充剂之间的相互作用会对患者产生负面影响。由于医疗保健提供者采用电子医疗记录和患者使用个人健康记录,有必要在这一范围内进行协调。在这种情况下,通过自动协调统一来自多个来源的信息可以解决药物不良反应,跟踪药物不良反应,并避免过度用药。这需要减轻多个数据源和系统的集成问题。在本文中,我们利用哈佛大学的SMART框架跨不同数据源执行药物调节,其长期目标是为过度用药和不良相互作用提供强大的决策支持。我们的原型应用SMARTSync提供了基于本体的交互识别、决策支持,并能够警告患者(或通知提供商)潜在的药物问题。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
SMARTSync: Towards patient-driven medication reconciliation
Interactions between prescription medications, over-the-counter drugs, and nutritional supplements can have negative consequences for patients. There is a need for the reconciliation across this spectrum spurred on by the adoption of electronic medical records by healthcare providers and the usage of personal health records by patients. In such a setting, unifying information from multiple sources through automated reconciliation can address adverse medication interactions, track adverse medication reactions, and avoid overmedication. This requires mitigating the integration issues of multiple data sources and systems. In this paper, we leverage Harvard University's SMART framework to perform medication reconciliation across different data sources, with the long-term goal of providing robust decision support for overmedication and adverse interactions. Our prototype application SMARTSync provides ontology-backed recognition of interactions, decision support, and is able to warn a patient (or notify a provider) of potential medication problems.
求助全文
通过发布文献求助,成功后即可免费获取论文全文。 去求助
来源期刊
自引率
0.00%
发文量
0
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
联系我们:info@booksci.cn Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。 Copyright © 2023 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术官方微信