基于DW的医院主动服务系统的研究与实现
摘要
随着计算机技术的进步,医院信息化程度的不断深入,各个医院都建立了自己的医院信息系统并积累了大量的医疗数据资源。若能从这些大量的医疗数据资源中挖掘出有用的信息辅助决策、辅助诊断,则可满足医院管理决策的需要、从而提高医疗质量,创造经济效益,并使医院和患者达到双赢的目标。
本课题的研究目标是在这些庞大的医疗数据资源建立起来的数据仓库上使用先进的数据挖掘技术,改变传统信息服务模式,设计一个商务智能化的医院主动信息服务系统,为医院信息系统提出主动服务的新应用模式和平台并找到行之有效的解决方案。
本文通过对数据仓库技术、数据挖掘中关联规则技术的研究和应用,提出一种商务智能的医院主动服务系统模式,并结合医院信息系统对其实现进行了探索。该系统是一套智能化系统,主动服务系统功能将渗透到医院管理决策支持、临床医疗技术支持、设备物质管理、财务业务管理、病人咨询服务等临床医疗活动各个方面,并包含:医院质量管理、医院经营目标管理、经营决策管理、医院资源管理、财务管理和预警系统六个功能模块,各个模块中的功能会在调研中继续加以完善。
论文的主要贡献表现在以下几个方面:
1、分析医院主动服务需求,并结合医院信息系统的实际数据,研究和确定可行的且有价值的挖掘主题并针对主题采集数据,建立医疗数据仓库。
2、根据实际挖掘应用选择相应适合的挖掘算法,深入研究关联规则挖掘技术并展示挖掘结果对医院管理和医疗决策带来的支持和帮助。
3、利用网络、移动服务等各种手段,建立医疗预警系统。
With the development in computer technology, hospital information data more to deepen, many hospitals have set up their own hospital information system and accumulated a large amount of data resources. The useful information be excavated from these large amount of data resources, it can support doctor diagnosis of the disease and help hospital's requirement of management. So as to improve the quality of treatment, to create economic benefits and let hospital and sick all can get what there want to have.
The subject of this research is to use advanced data mining technology base on, change the traditional mode of information service, to design a intelligent business initiative of the hospital information system.
This article through the data warehouse technology, mining association rules technology of data mining, decision tree mining technology to depth study, according to the development and trends of China's medical and health sector and information technology, combination the characteristics of hospital clinical activities, it to bring a system model in business Intelligence of hospital. It to combine hospital information system and to search for whether could let it realize. The system is a set of intelligent system, active service capability would to infiltrate in various aspects of hospital clinical activities, for example decision Support management, clinical Support, material management, financial management and patients advisory services and so on. It includes hospital quality management, hospital operation objectives management, operating decision-making management, hospital resources management, financial Management and early warning system. I will continue to improve research of each module. The main contributions in this thesis are as follows:
1) Analysis of the demand for hospital services initiative and set up medical data warehouse system combined with real data of hospital information systems and collecting data through researching and identifing viable and valuable mining theme .
2) In-depth study of association rule and techniques of mining according to the appropriate application of the actual excavation for the mining algorithm, and value the impact to hospital management and medical decision-making brought about by data mining.
3) Establish medical warning system by the Internet, mobile services and other kind of means.
本课题的研究目标是在这些庞大的医疗数据资源建立起来的数据仓库上使用先进的数据挖掘技术,改变传统信息服务模式,设计一个商务智能化的医院主动信息服务系统,为医院信息系统提出主动服务的新应用模式和平台并找到行之有效的解决方案。
本文通过对数据仓库技术、数据挖掘中关联规则技术的研究和应用,提出一种商务智能的医院主动服务系统模式,并结合医院信息系统对其实现进行了探索。该系统是一套智能化系统,主动服务系统功能将渗透到医院管理决策支持、临床医疗技术支持、设备物质管理、财务业务管理、病人咨询服务等临床医疗活动各个方面,并包含:医院质量管理、医院经营目标管理、经营决策管理、医院资源管理、财务管理和预警系统六个功能模块,各个模块中的功能会在调研中继续加以完善。
论文的主要贡献表现在以下几个方面:
1、分析医院主动服务需求,并结合医院信息系统的实际数据,研究和确定可行的且有价值的挖掘主题并针对主题采集数据,建立医疗数据仓库。
2、根据实际挖掘应用选择相应适合的挖掘算法,深入研究关联规则挖掘技术并展示挖掘结果对医院管理和医疗决策带来的支持和帮助。
3、利用网络、移动服务等各种手段,建立医疗预警系统。
With the development in computer technology, hospital information data more to deepen, many hospitals have set up their own hospital information system and accumulated a large amount of data resources. The useful information be excavated from these large amount of data resources, it can support doctor diagnosis of the disease and help hospital's requirement of management. So as to improve the quality of treatment, to create economic benefits and let hospital and sick all can get what there want to have.
The subject of this research is to use advanced data mining technology base on, change the traditional mode of information service, to design a intelligent business initiative of the hospital information system.
This article through the data warehouse technology, mining association rules technology of data mining, decision tree mining technology to depth study, according to the development and trends of China's medical and health sector and information technology, combination the characteristics of hospital clinical activities, it to bring a system model in business Intelligence of hospital. It to combine hospital information system and to search for whether could let it realize. The system is a set of intelligent system, active service capability would to infiltrate in various aspects of hospital clinical activities, for example decision Support management, clinical Support, material management, financial management and patients advisory services and so on. It includes hospital quality management, hospital operation objectives management, operating decision-making management, hospital resources management, financial Management and early warning system. I will continue to improve research of each module. The main contributions in this thesis are as follows:
1) Analysis of the demand for hospital services initiative and set up medical data warehouse system combined with real data of hospital information systems and collecting data through researching and identifing viable and valuable mining theme .
2) In-depth study of association rule and techniques of mining according to the appropriate application of the actual excavation for the mining algorithm, and value the impact to hospital management and medical decision-making brought about by data mining.
3) Establish medical warning system by the Internet, mobile services and other kind of means.
引文
[1]徐建军.医院信息系统中的挖掘技术研究[M].浙江大学硕士学位论文,2006
[2]李伟.陈雄鹰编著企业IT战略与决策机械工业出版社,2005
[3]彭木根等.数据仓库技术与实现[M].北京:电子工业出版社,2002.
[4]Chaudhuri S,Dayal U.An Overview of DataWarehousing and OLAPTechnology[J].SIGMOD Record,1997:134-147.
[5]郑斌祥,席裕庚,杜秀华.基于面向对象技术的OLAP系统设计研究及应用[J].计算机工程,2001,27(11):153-155.
[6]Hasan H,Hyland P.Using OLAP and multidimensional data for decision making[J].IT Professional,2001:85-88.
[7]W.H.Inmon.Building the Data Warehouse[M].北京:机械工业出版社,2000.
[8]美国国防部建立医学数据库模型.http://www.costind.gov.cn/n435777/n435943/n435949/n435995/93308.html
[9]福州军区总医院信息系统发展概述.http://www.ccw.com.cn/cio/research/info/htm2004/20040823-130GX.asp
[10]Sacha JP,Goodenday I_S,Cios KJ.Bayesian learning for cardiac SPELT image InterpretationEJ].Artif Intell Med,2002,26(1-2):109-143.
[11]Ganzert S,Guttmann J,Kersting K,et al.Analysis of respiratory pressure-volume curves in intensive care medicine using inductive machine learning[J].Artif Intell Med,2002,26(12):69-86.
[12]Imherman SP,Domanski B,Thompson HW.Using dependency/association rules to find indications for computed topography in a head trauma dataset[J].Artif Intell Med,2002,26(12):55-68.
[13]Evans S,Lemon SJ,Deters CA,et al.Automated detection of hereditary syndromes using data mining[J].Compute Biomed Res,1997,30(5):337-348.
[14]Mapel DW,Coultas DB.Ethnic differences in the prevalence of nonmalignant respiratory disease among uranium miners[J].Public health,1997,87(5):833-838.
[15]乔延江,李澎涛,苏刚强.中药(复方)KDD研究开发的意义[J].北京中医药大学报,1998,21(3):15-17.
[16]屈景辉,廖琪梅,许卫中.医学信息数据库的建立与数据挖掘[J].第四军医大学学报,2001,22(1):88-89.
[17]中华人民共和国卫生部版权所有.医院信息系统基本功能规范[S].
[18]http://info.med.hc360.com/2005/05/10104263842-3.shtml李包罗.我国医院信息系统(His)投资见高潮.
[19]徐昀.医院信息系统实施中的几个问题[J].中华医院管理杂志,2005(4):18.
[20]赵辉.漳州市医院信息系统设计方案[Z].厦门智业软件有限公司,2006.
[21]方天宇.数据挖掘技术在医院信息系统中的应用[D].哈尔滨工程大学工程硕士学位论文,2007.
[22]赵玉兰.电子病历一卡通系统的研究[D].哈尔滨理工大学工程硕士学位论文,2007.
[23]袁捷,陆菊康,邵伟民等.一个基于面向对象方法的智能决策支持系统生成器[J].2001,27(2):50-52.
[24]李斌.金融时间序列挖掘关键算法研究[D].中国科学技术大学,2002.
[25]胡桔州,兰秋军.金融时间序列的数据挖掘技术与经典统计模型的比较[J].系统工程,2005,23(6):95-98.
[26]来升强,朱建平.数据挖掘中高维定性数据的粗糙集聚类统计研究[J].统计研究,2005(8):56-60.
[27]Heckerman D.Bayesian networks for data mining[J].Data Mining and Knowledge Discovery,1997(1):79-119.
[28]Apte CH,Weiss S.Data mining with decision trees and decision Rules[J].Future Generation Computer Systems Elsevier,1997(13):197.
[29]林士敏,田风占,陆玉昌.贝叶斯学习、贝叶斯网络与数据采掘[J].计算机科学,2000,27(10):69-72.
[30]王实,高文.数据挖掘中的聚类方法[J].计算机科学,2000,27(4):42-45.
[31]Leung Y,Ma J H,Zhang W X.A new method for mining regression classes in large data sets[J].Trans Pattern Analysis and MachineIntelligence,2001,23(1):5-21.
[32]吕安民,李成名,林宗坚等.基于统计归纳学习的GIS属性数据挖掘[J].测绘学院学报,2001,18(4):290-293.
[33]JiaWeiHan.,Michel ine Kamber著.范明,孟小峰等译.数据挖掘概念与技术[M].北京:机械工业出版社,2001.
[34]洪建白.短信服务功能模块系统文档[z].厦门智业软件有限公司,2007.
[35]W.H.Inmon.Building the Data Warehouse Third Edition[M].机械工业出版社,2005.
[36]JiaWeiHan.,Micheline Kamber著.范明,孟小峰等译.数据挖掘概念与技术[M].北京:机械工业出版社,2001.
[37]钱崇强.数据仓库技术在医院应用中的研究[D].天津大学硕士学位论文,2005.
[38]林杰斌,刘明德,陈湘.数据挖掘与OLAP理论与务实[M].清华大学出版社,2002.
[39]肖冰.医疗数据仓库的设计[D].长春工业大学硕士学位论文,2004.
[40]汪小飞.数据仓库之路[G].http://www.dwway.com/html/20/n-2820.html.2005
[41]钟爱军,宋麒.基于数据仓库的医院决策支持系统的构建[J].临床医学,2006(5):18-19.
[42]于宗民,刘义宁,祁国辉.数据仓库项目管理实践[M].人民邮电出版社,2005.
[43]苏新宁,杨建林,江念南,粟湘.数据仓库和数据挖掘技术.清华大学出版社,2006.
[44]http://percywang.itpub.net/post/25150/262821商业智能常用词汇大全.
[45]毕雪华,森干.数据挖掘技术在医学领域中的应用[J].电脑知识与技术,2007.
[46]Han Jiawei,Kamber M.Data Mining:Concepts and Techniques[J].Simon Fraser University,2000.
[47]易静.医院信息数据挖掘及实现技术的探索[D].重庆医科大学博士学位论文,2007.
[48]付光金.HIS中医疗费用的数据挖掘[D].吉林大学硕士论文,2005.
[49]Hinneburg A et al.An efficient approach to clustering in large multimedia databases[J].In Proc 1998 Int.Conf Knowledge Discovery and Data Mining.New York,USA Aug.1998:58-65.
[50]胡侃,夏绍玮.基于大型数据仓库的数据采掘研究综述[J].软件学报,1998(9):53-63.
[51]王雷.HIS中的数据挖掘[J].现代医院,2006(11):138-139.
[52]张松,祝扬,聂哲,王树明.采用数据挖掘技术辅助制定医院运营战略目标[J].中华医学科研管理杂志,2005(10):272-275.
[53]石义芳.引用于数据挖掘技术在病人流量分析中的应用研究[D].暨南大学硕士学位论文,2006.
[54]付阶辉,赵林度.数据挖掘技术在HIS中的应用[J].东南大学学报(哲学社会科学版),2002.4(增刊):80-84.
[2]李伟.陈雄鹰编著企业IT战略与决策机械工业出版社,2005
[3]彭木根等.数据仓库技术与实现[M].北京:电子工业出版社,2002.
[4]Chaudhuri S,Dayal U.An Overview of DataWarehousing and OLAPTechnology[J].SIGMOD Record,1997:134-147.
[5]郑斌祥,席裕庚,杜秀华.基于面向对象技术的OLAP系统设计研究及应用[J].计算机工程,2001,27(11):153-155.
[6]Hasan H,Hyland P.Using OLAP and multidimensional data for decision making[J].IT Professional,2001:85-88.
[7]W.H.Inmon.Building the Data Warehouse[M].北京:机械工业出版社,2000.
[8]美国国防部建立医学数据库模型.http://www.costind.gov.cn/n435777/n435943/n435949/n435995/93308.html
[9]福州军区总医院信息系统发展概述.http://www.ccw.com.cn/cio/research/info/htm2004/20040823-130GX.asp
[10]Sacha JP,Goodenday I_S,Cios KJ.Bayesian learning for cardiac SPELT image InterpretationEJ].Artif Intell Med,2002,26(1-2):109-143.
[11]Ganzert S,Guttmann J,Kersting K,et al.Analysis of respiratory pressure-volume curves in intensive care medicine using inductive machine learning[J].Artif Intell Med,2002,26(12):69-86.
[12]Imherman SP,Domanski B,Thompson HW.Using dependency/association rules to find indications for computed topography in a head trauma dataset[J].Artif Intell Med,2002,26(12):55-68.
[13]Evans S,Lemon SJ,Deters CA,et al.Automated detection of hereditary syndromes using data mining[J].Compute Biomed Res,1997,30(5):337-348.
[14]Mapel DW,Coultas DB.Ethnic differences in the prevalence of nonmalignant respiratory disease among uranium miners[J].Public health,1997,87(5):833-838.
[15]乔延江,李澎涛,苏刚强.中药(复方)KDD研究开发的意义[J].北京中医药大学报,1998,21(3):15-17.
[16]屈景辉,廖琪梅,许卫中.医学信息数据库的建立与数据挖掘[J].第四军医大学学报,2001,22(1):88-89.
[17]中华人民共和国卫生部版权所有.医院信息系统基本功能规范[S].
[18]http://info.med.hc360.com/2005/05/10104263842-3.shtml李包罗.我国医院信息系统(His)投资见高潮.
[19]徐昀.医院信息系统实施中的几个问题[J].中华医院管理杂志,2005(4):18.
[20]赵辉.漳州市医院信息系统设计方案[Z].厦门智业软件有限公司,2006.
[21]方天宇.数据挖掘技术在医院信息系统中的应用[D].哈尔滨工程大学工程硕士学位论文,2007.
[22]赵玉兰.电子病历一卡通系统的研究[D].哈尔滨理工大学工程硕士学位论文,2007.
[23]袁捷,陆菊康,邵伟民等.一个基于面向对象方法的智能决策支持系统生成器[J].2001,27(2):50-52.
[24]李斌.金融时间序列挖掘关键算法研究[D].中国科学技术大学,2002.
[25]胡桔州,兰秋军.金融时间序列的数据挖掘技术与经典统计模型的比较[J].系统工程,2005,23(6):95-98.
[26]来升强,朱建平.数据挖掘中高维定性数据的粗糙集聚类统计研究[J].统计研究,2005(8):56-60.
[27]Heckerman D.Bayesian networks for data mining[J].Data Mining and Knowledge Discovery,1997(1):79-119.
[28]Apte CH,Weiss S.Data mining with decision trees and decision Rules[J].Future Generation Computer Systems Elsevier,1997(13):197.
[29]林士敏,田风占,陆玉昌.贝叶斯学习、贝叶斯网络与数据采掘[J].计算机科学,2000,27(10):69-72.
[30]王实,高文.数据挖掘中的聚类方法[J].计算机科学,2000,27(4):42-45.
[31]Leung Y,Ma J H,Zhang W X.A new method for mining regression classes in large data sets[J].Trans Pattern Analysis and MachineIntelligence,2001,23(1):5-21.
[32]吕安民,李成名,林宗坚等.基于统计归纳学习的GIS属性数据挖掘[J].测绘学院学报,2001,18(4):290-293.
[33]JiaWeiHan.,Michel ine Kamber著.范明,孟小峰等译.数据挖掘概念与技术[M].北京:机械工业出版社,2001.
[34]洪建白.短信服务功能模块系统文档[z].厦门智业软件有限公司,2007.
[35]W.H.Inmon.Building the Data Warehouse Third Edition[M].机械工业出版社,2005.
[36]JiaWeiHan.,Micheline Kamber著.范明,孟小峰等译.数据挖掘概念与技术[M].北京:机械工业出版社,2001.
[37]钱崇强.数据仓库技术在医院应用中的研究[D].天津大学硕士学位论文,2005.
[38]林杰斌,刘明德,陈湘.数据挖掘与OLAP理论与务实[M].清华大学出版社,2002.
[39]肖冰.医疗数据仓库的设计[D].长春工业大学硕士学位论文,2004.
[40]汪小飞.数据仓库之路[G].http://www.dwway.com/html/20/n-2820.html.2005
[41]钟爱军,宋麒.基于数据仓库的医院决策支持系统的构建[J].临床医学,2006(5):18-19.
[42]于宗民,刘义宁,祁国辉.数据仓库项目管理实践[M].人民邮电出版社,2005.
[43]苏新宁,杨建林,江念南,粟湘.数据仓库和数据挖掘技术.清华大学出版社,2006.
[44]http://percywang.itpub.net/post/25150/262821商业智能常用词汇大全.
[45]毕雪华,森干.数据挖掘技术在医学领域中的应用[J].电脑知识与技术,2007.
[46]Han Jiawei,Kamber M.Data Mining:Concepts and Techniques[J].Simon Fraser University,2000.
[47]易静.医院信息数据挖掘及实现技术的探索[D].重庆医科大学博士学位论文,2007.
[48]付光金.HIS中医疗费用的数据挖掘[D].吉林大学硕士论文,2005.
[49]Hinneburg A et al.An efficient approach to clustering in large multimedia databases[J].In Proc 1998 Int.Conf Knowledge Discovery and Data Mining.New York,USA Aug.1998:58-65.
[50]胡侃,夏绍玮.基于大型数据仓库的数据采掘研究综述[J].软件学报,1998(9):53-63.
[51]王雷.HIS中的数据挖掘[J].现代医院,2006(11):138-139.
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