{"title":"将ICD-9和ICD-10数据整合到一个仓库中","authors":"Johann Eder, Christian Koncilia","doi":"10.1109/CBMS.2002.1011360","DOIUrl":null,"url":null,"abstract":"The shift from version 9 to version 10 of the \"International Statistical Classification of Diseases and Related Health Problems\", or ICD (International Classification of Diseases) for short, causes enormous problems for the exploitation of medical data warehouses, since conventional data warehouses do not support the change of the structure of dimensions, i.e. the content and relationships of master data like the diagnostic codes, or other key values. This shortcoming results in a reduction of possible analysis, and unfortunately is the cause of many wrong statistics and analysis results. In this paper, we analyze the problem and show how to superimpose conventional multi-dimensional data warehouses with temporal master data to allow queries spanning multiple periods to return correct answers.","PeriodicalId":369629,"journal":{"name":"Proceedings of 15th IEEE Symposium on Computer-Based Medical Systems (CBMS 2002)","volume":"41 233 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2002-06-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"3","resultStr":"{\"title\":\"Incorporating ICD-9 and ICD-10 data in a warehouse\",\"authors\":\"Johann Eder, Christian Koncilia\",\"doi\":\"10.1109/CBMS.2002.1011360\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"The shift from version 9 to version 10 of the \\\"International Statistical Classification of Diseases and Related Health Problems\\\", or ICD (International Classification of Diseases) for short, causes enormous problems for the exploitation of medical data warehouses, since conventional data warehouses do not support the change of the structure of dimensions, i.e. the content and relationships of master data like the diagnostic codes, or other key values. This shortcoming results in a reduction of possible analysis, and unfortunately is the cause of many wrong statistics and analysis results. In this paper, we analyze the problem and show how to superimpose conventional multi-dimensional data warehouses with temporal master data to allow queries spanning multiple periods to return correct answers.\",\"PeriodicalId\":369629,\"journal\":{\"name\":\"Proceedings of 15th IEEE Symposium on Computer-Based Medical Systems (CBMS 2002)\",\"volume\":\"41 233 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2002-06-04\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"3\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Proceedings of 15th IEEE Symposium on Computer-Based Medical Systems (CBMS 2002)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/CBMS.2002.1011360\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Proceedings of 15th IEEE Symposium on Computer-Based Medical Systems (CBMS 2002)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/CBMS.2002.1011360","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Incorporating ICD-9 and ICD-10 data in a warehouse
The shift from version 9 to version 10 of the "International Statistical Classification of Diseases and Related Health Problems", or ICD (International Classification of Diseases) for short, causes enormous problems for the exploitation of medical data warehouses, since conventional data warehouses do not support the change of the structure of dimensions, i.e. the content and relationships of master data like the diagnostic codes, or other key values. This shortcoming results in a reduction of possible analysis, and unfortunately is the cause of many wrong statistics and analysis results. In this paper, we analyze the problem and show how to superimpose conventional multi-dimensional data warehouses with temporal master data to allow queries spanning multiple periods to return correct answers.