Big Data as a Driver for Clinical Decision Support Systems: A Learning Health Systems Perspective

A. Dagliati, V. Tibollo, L. Sacchi, A. Malovini, I. Limongelli, Matteo Gabetta, C. Napolitano, A. Mazzanti, P. D. Cata, L. Chiovato, S. Priori, R. Bellazzi
{"title":"Big Data as a Driver for Clinical Decision Support Systems: A Learning Health Systems Perspective","authors":"A. Dagliati, V. Tibollo, L. Sacchi, A. Malovini, I. Limongelli, Matteo Gabetta, C. Napolitano, A. Mazzanti, P. D. Cata, L. Chiovato, S. Priori, R. Bellazzi","doi":"10.3389/fdigh.2018.00008","DOIUrl":null,"url":null,"abstract":"Big data technologies are nowadays providing health care with powerful instruments to gather and analyze large volumes of heterogeneous data collected for different purposes, including clinical care, administration and research. This makes possible to design IT infrastructures that favor the implementation of the so-called \"Learning Healthcare System Cycle\", where healthcare practice and research are part of a unique and synergic process. In this paper we highlight how \"Big Data enabled\" integrated data collections may support clinical decision-making together with biomedical research. Two effective implementations are reported, concerning decision support in Diabetes and in Inherited Arrhythmogenic Diseases.","PeriodicalId":227954,"journal":{"name":"Frontiers Digit. Humanit.","volume":"48 3 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2018-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"27","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Frontiers Digit. Humanit.","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.3389/fdigh.2018.00008","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 27

Abstract

Big data technologies are nowadays providing health care with powerful instruments to gather and analyze large volumes of heterogeneous data collected for different purposes, including clinical care, administration and research. This makes possible to design IT infrastructures that favor the implementation of the so-called "Learning Healthcare System Cycle", where healthcare practice and research are part of a unique and synergic process. In this paper we highlight how "Big Data enabled" integrated data collections may support clinical decision-making together with biomedical research. Two effective implementations are reported, concerning decision support in Diabetes and in Inherited Arrhythmogenic Diseases.
大数据作为临床决策支持系统的驱动因素:学习健康系统的视角
如今,大数据技术为医疗保健提供了强大的工具,可以收集和分析为不同目的(包括临床护理、管理和研究)收集的大量异构数据。这使得设计有利于实现所谓的“学习医疗保健系统周期”的IT基础设施成为可能,其中医疗保健实践和研究是独特的协同过程的一部分。在本文中,我们强调了“大数据支持”集成数据收集如何支持临床决策以及生物医学研究。关于糖尿病和遗传性心律失常疾病的决策支持,报道了两种有效的实施方法。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
求助全文
约1分钟内获得全文 求助全文
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