中国数字医学
中國數字醫學
중국수자의학
CHINA DIGITAL MEDICINE
2014年
8期
49-51,60
,共4页
朱远燕%林德南%陈汝林%王爽%郑静
硃遠燕%林德南%陳汝林%王爽%鄭靜
주원연%림덕남%진여림%왕상%정정
区域卫生%数据中心%业务协同%实时查询交换%SolrCloud
區域衛生%數據中心%業務協同%實時查詢交換%SolrCloud
구역위생%수거중심%업무협동%실시사순교환%SolrCloud
regional health%data center%business cooperation%real-time query and exchange%SolrCloud
随着区域医疗业务增长迅速,区域内医疗机构之间对于医疗信息共享的需求越来越迫切,然而各个医疗机构业务系统构建技术不同,现有基于传统数据库构建的区域医疗信息查询系统已不能满足高并发实时随机医疗信息的查询和交换需求。提出了一种由SolrCloud构建分布式区域海量医疗患者信息的实时查询交换系统,运用该软件提供的高效动态协调能力、高速索引同步能力、高可用性和容灾备份能力,解决区域内医疗机构向数据中心高并发数据查询交换的需求瓶颈,提升区域实时医疗业务协同能力。最后以该系统最频繁使用的MPI(病人主索引)实时构建和查询交换模块为例,验证SolrCloud架构在区域医疗机构高并发实时查询和交换的性能。
隨著區域醫療業務增長迅速,區域內醫療機構之間對于醫療信息共享的需求越來越迫切,然而各箇醫療機構業務繫統構建技術不同,現有基于傳統數據庫構建的區域醫療信息查詢繫統已不能滿足高併髮實時隨機醫療信息的查詢和交換需求。提齣瞭一種由SolrCloud構建分佈式區域海量醫療患者信息的實時查詢交換繫統,運用該軟件提供的高效動態協調能力、高速索引同步能力、高可用性和容災備份能力,解決區域內醫療機構嚮數據中心高併髮數據查詢交換的需求瓶頸,提升區域實時醫療業務協同能力。最後以該繫統最頻繁使用的MPI(病人主索引)實時構建和查詢交換模塊為例,驗證SolrCloud架構在區域醫療機構高併髮實時查詢和交換的性能。
수착구역의료업무증장신속,구역내의료궤구지간대우의료신식공향적수구월래월박절,연이각개의료궤구업무계통구건기술불동,현유기우전통수거고구건적구역의료신식사순계통이불능만족고병발실시수궤의료신식적사순화교환수구。제출료일충유SolrCloud구건분포식구역해량의료환자신식적실시사순교환계통,운용해연건제공적고효동태협조능력、고속색인동보능력、고가용성화용재비빈능력,해결구역내의료궤구향수거중심고병발수거사순교환적수구병경,제승구역실시의료업무협동능력。최후이해계통최빈번사용적MPI(병인주색인)실시구건화사순교환모괴위례,험증SolrCloud가구재구역의료궤구고병발실시사순화교환적성능。
With the rapid growth in regional medical business, medical information sharing among medical institutions has become more and more urgent. However, the technologies which medical institutions are using for building medical business systems are different, and the existing regional medical information system based on traditional database cannot match high concurrency real-time exchange and query requirements. This paper aims to build a distributed massive medical information query and exchange system based on SolrCloud, which has efficient and dynamic coordination ability, high speed index synchronization ability, high availability and disaster tolerance ability, and aims to solve the high concurrency exchange bottleneck between medical institutions and data center and realize medical business cooperation. In the end, taking the most frequently used MPI (Master Patient Index) building and querying module as an example, the performance of SolrCloud architecture in high concurrency real-time query and exchange was validated.