{"title":"利用时态数据挖掘表征医院服务","authors":"S. Tsumoto, S. Hirano, H. Iwata, Y. Tsumoto","doi":"10.1109/SRII.2012.105","DOIUrl":null,"url":null,"abstract":"Computerization of hospital information enables us to visualize and analyze temporal characteristics of hospital services, which can be viewed as a first step to improve and innovate clinical services. This paper proposes a temporal data mining process which consists of decision tree, clustering, MDS and three-dimensional trajectories mining and applied the method to datasets extracted from hospital information systems. The results show that the reuse of stored data will give a powerful tool to characterize medical services in the following ways: (1) Statistics and temporal characteristics of clinincal orders were visualized. (2) Divisions were classified in terms of temporal patterns of orders. (3) The temporal interval important to characterize the behavior of the divisions were evaluated. (4) Characterization of nursing orders showed the classification of nursing orders into disease-specific ones and patient- specific ones.","PeriodicalId":110778,"journal":{"name":"2012 Annual SRII Global Conference","volume":"16 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2012-07-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"5","resultStr":"{\"title\":\"Characterizing Hospital Services Using Temporal Data Mining\",\"authors\":\"S. Tsumoto, S. Hirano, H. Iwata, Y. Tsumoto\",\"doi\":\"10.1109/SRII.2012.105\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Computerization of hospital information enables us to visualize and analyze temporal characteristics of hospital services, which can be viewed as a first step to improve and innovate clinical services. This paper proposes a temporal data mining process which consists of decision tree, clustering, MDS and three-dimensional trajectories mining and applied the method to datasets extracted from hospital information systems. The results show that the reuse of stored data will give a powerful tool to characterize medical services in the following ways: (1) Statistics and temporal characteristics of clinincal orders were visualized. (2) Divisions were classified in terms of temporal patterns of orders. (3) The temporal interval important to characterize the behavior of the divisions were evaluated. (4) Characterization of nursing orders showed the classification of nursing orders into disease-specific ones and patient- specific ones.\",\"PeriodicalId\":110778,\"journal\":{\"name\":\"2012 Annual SRII Global Conference\",\"volume\":\"16 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2012-07-24\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"5\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2012 Annual SRII Global Conference\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/SRII.2012.105\",\"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 Annual SRII Global Conference","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/SRII.2012.105","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Characterizing Hospital Services Using Temporal Data Mining
Computerization of hospital information enables us to visualize and analyze temporal characteristics of hospital services, which can be viewed as a first step to improve and innovate clinical services. This paper proposes a temporal data mining process which consists of decision tree, clustering, MDS and three-dimensional trajectories mining and applied the method to datasets extracted from hospital information systems. The results show that the reuse of stored data will give a powerful tool to characterize medical services in the following ways: (1) Statistics and temporal characteristics of clinincal orders were visualized. (2) Divisions were classified in terms of temporal patterns of orders. (3) The temporal interval important to characterize the behavior of the divisions were evaluated. (4) Characterization of nursing orders showed the classification of nursing orders into disease-specific ones and patient- specific ones.