挖掘医疗管理数据- PKB套件

Aaron Ceglar, R. Morrall, J. Roddick
{"title":"挖掘医疗管理数据- PKB套件","authors":"Aaron Ceglar, R. Morrall, J. Roddick","doi":"10.3233/978-1-60750-633-1-110","DOIUrl":null,"url":null,"abstract":"Hospitals are adept at capturing large volumes of highly multi-dimensional data about their activities including clinical, demographic, administrative, financial and, increasingly, outcome data (such as adverse events). Managing and understanding this data is difficult as hospitals typically do not have the staff and/or the expertise to assemble, query, analyse and report on the potential knowledge contained within such data. The Power Knowledge Builder (PKB) project investigated the adaption of data mining algorithms to the domain of patient costing, with the aim of helping practitioners better understand their data and therefore facilitate best practice.","PeriodicalId":438467,"journal":{"name":"Data Mining for Business Applications","volume":"2 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2010-08-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"3","resultStr":"{\"title\":\"Mining Medical Administrative Data - The PKB Suite\",\"authors\":\"Aaron Ceglar, R. Morrall, J. Roddick\",\"doi\":\"10.3233/978-1-60750-633-1-110\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Hospitals are adept at capturing large volumes of highly multi-dimensional data about their activities including clinical, demographic, administrative, financial and, increasingly, outcome data (such as adverse events). Managing and understanding this data is difficult as hospitals typically do not have the staff and/or the expertise to assemble, query, analyse and report on the potential knowledge contained within such data. The Power Knowledge Builder (PKB) project investigated the adaption of data mining algorithms to the domain of patient costing, with the aim of helping practitioners better understand their data and therefore facilitate best practice.\",\"PeriodicalId\":438467,\"journal\":{\"name\":\"Data Mining for Business Applications\",\"volume\":\"2 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2010-08-07\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"3\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Data Mining for Business Applications\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.3233/978-1-60750-633-1-110\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Data Mining for Business Applications","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.3233/978-1-60750-633-1-110","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 3

摘要

医院擅长获取有关其活动的大量高度多维数据,包括临床、人口、行政、财务以及越来越多的结果数据(如不良事件)。管理和理解这些数据是困难的,因为医院通常没有工作人员和/或专业知识来收集、查询、分析和报告这些数据中包含的潜在知识。Power Knowledge Builder (PKB)项目调查了数据挖掘算法在患者成本计算领域的应用,目的是帮助从业者更好地理解他们的数据,从而促进最佳实践。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
查看原文
分享 分享
微信好友 朋友圈 QQ好友 复制链接
本刊更多论文
Mining Medical Administrative Data - The PKB Suite
Hospitals are adept at capturing large volumes of highly multi-dimensional data about their activities including clinical, demographic, administrative, financial and, increasingly, outcome data (such as adverse events). Managing and understanding this data is difficult as hospitals typically do not have the staff and/or the expertise to assemble, query, analyse and report on the potential knowledge contained within such data. The Power Knowledge Builder (PKB) project investigated the adaption of data mining algorithms to the domain of patient costing, with the aim of helping practitioners better understand their data and therefore facilitate best practice.
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
期刊最新文献
Customer churn prediction - a case study in retail banking Towards the Generic Framework for Utility Considerations in Data Mining Research Data Mining for Business Applications: Introduction Forecasting Online Auctions using Dynamic Models Interactivity Closes the Gap - Lessons Learned in an Automotive Industry Application
×
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
现在去查看 取消
×
提示
确定
0
微信
客服QQ
Book学术公众号 扫码关注我们
反馈
×
意见反馈
请填写您的意见或建议
请填写您的手机或邮箱
已复制链接
已复制链接
快去分享给好友吧!
我知道了
×
扫码分享
扫码分享
Book学术官方微信
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术
文献互助 智能选刊 最新文献 互助须知 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 Book学术 All rights reserved.
ghs 京公网安备 11010802042870号 京ICP备2023020795号-1