Multimorbidity Clusters: Clustering Binary Data From Multimorbidity Clusters: Clustering Binary Data From a Large Administrative Medical Database

Multimorbidity Clusters: Clustering Binary Data From Multimorbidity Clusters: Clustering Binary Data From a Large Administrative Medical Database
复制标题

多病态聚类:对来自多病态聚类的二进制数据进行聚类:对来自大型管理医疗数据库的二进制数据进行聚类

DOI:
--
复制
发表时间:
2009
期刊:
Adaptive Multimedia Retrieval
影响因子:
--
通讯作者:
P. Noël
P. Noël
中科院分区:
--
文献类型:
--
作者:
J. Cornell;J. Pugh;John Williams;L. Kazis;A. Lee;M. Parchman;J. Zeber;Thomas G Pederson;K. Montgomery;P. Noël

文献摘要

参考文献

被引文献

相似文献

我们在本文中的目的是描述和说明聚类分析在识别临床相关的多发病群体中的应用。多重发病是指一个人体内同时出现两种或多种疾病,这就提出了一个问题:在慢性疾病组中是否存在一致的、临床上有用的多重发病组。我们在本文中的目的是描述和说明聚类分析在识别临床相关的多发病群体中的应用。聚类分析的应用涉及一系列关键的方法和分析决策,这些决策影响所产生的聚类的质量和意义。我们举例说明了聚类分析的应用,以识别由退伍军人健康管理局服务的初级保健患者 (N = 1,327,328) 中患有 2 种或更多慢性病的 45 种慢性病中的多发病簇。确定了六个临床上有用的多发病簇:代谢簇、肥胖簇、肝脏簇、神经血管簇、应激簇和双重诊断簇。聚类分析似乎是识别多种疾病集群和多发病模式的有用技术。
Our purpose in this article is to describe and illustrate the application of cluster analysis to identify clinically relevant multimorbidity groups. Multimorbidity is the co-occurrence of 2 or more illnesses within a single person, which raises the question whether consistent, clinically useful multimorbidity groups exist among sets of chronic illnesses. Our purpose in this article is to describe and illustrate the application of cluster analysis to identify clinically relevant multimorbidity groups. Application of cluster analysis involves a sequence of critical methodological and analytic decisions that influence the quality and meaning of the clusters produced. We illustrate the application of cluster analysis to identify multimorbidity clusters in a set of 45 chronic illnesses in primary care patients (N = 1,327,328), with 2 or more chronic conditions, served by the Veterans Health Administration. Six clinically useful multimorbidity clusters were identified: a Metabolic Cluster, an Obesity Cluster, a Liver Cluster, a Neurovascular Cluster, a Stress Cluster and a Dual Diagnosis Cluster. Cluster analysis appears to be a useful technique for identifying multiple disease clusters and patterns of multimorbidity.
DOI: 10.1176/ps.47.8.853
发表时间: 1996-08
影响因子: 3.8
作者:
R. Owen;E. Fischer;B. Booth;B. Cuffel
通讯作者: R. Owen;E. Fischer;B. Booth;B. Cuffel
DOI: 10.1016/s0895-4356(98)00124-3
发表时间: 1999-01-01
影响因子: 7.2
作者:
Fried, LP;Bandeen-Roche, K;Guralnik, JM
通讯作者: Guralnik, JM
预测精神分裂症、情感分裂和情感障碍患者的“旋转门”现象。
DOI: 10.1176/ajp.152.6.856
发表时间: 1995
期刊: The American journal of psychiatry
影响因子: --
作者:
Haywood,TW;Kravitz,HM;Grossman,LS;CavanaughJr,JL;Davis,JM;Lewis,DA
通讯作者: Lewis,DA
精神分裂症患者的药物滥用:临床相关性和使用原因。
DOI: 10.1176/ajp.148.2.224
发表时间: 1991
期刊: The American journal of psychiatry
影响因子: --
作者:
Dixon,L;Haas,G;Weiden,PJ;Sweeney,J;Frances,AJ
通讯作者: Frances,AJ
DOI: 10.1073/pnas.95.25.14863
发表时间: 1998-12-08
影响因子: 11.1
作者:
Eisen, MB;Spellman, PT;Botstein, D
通讯作者: Botstein, D