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分析了医院信息化建设面临的问题,描述了集成平台目前的现状并对存在的问题进行了整理分析。分别针对基于HL7的一体化集成平台、基于SOA的医院集成平台、基于Portal引擎的集成平台的架构特点进行了讨论,为医院信息平台的建设提供了有价值的参考。 相似文献
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结合湘潭市中心医院实例,阐述医院信息平台总体架构、实现方法,包括信息集成、大数据服务、主数据管理、门户集成平台等,介绍建设步骤和效果,指出该平台对实现资源的精细管理和高效应用、提高医院整体水平具有重要意义。 相似文献
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目的:在医院内部信息系统集成方面,传统点对点接口通信模式存在系统耦合度高,系统整体稳定性和安全性难以预测和控制等隐患。不同业务系统之间难以实现数据交换与资源共享。如何打造一个稳定、高效、安全、可管理的集成平台,以满足不断变化的应用需求是一个亟待解决的问题。方法:将Ensemble集成平台技术引入到医院信息化建设中进行研究是一项非常有意义的工作,在分析传统点对点接口通信模式不足的基础上,文章结合Ensemble集成平台技术,建立了以病人为中心的统一视图,实现了跨平台的数据交换与共享。结果:通过Ensemble集成平台技术建立了以患者就诊流程为核心的内部信息共享交互平台,实现了全院数据交换与共享,消除了“信息孤岛”,实现了新业务应用的快速部署。结论:Ensemble集成平台技术为医院业务变革提供了灵活的、快速实施和部署的系统架构,实现了医疗信息的交换与共享,优化了服务流程,提高了医院运营效率,满足了医院信息化可持续发展。 相似文献
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Craig Barnes Binam Bajracharya Matthew Cannalte Zakir Gowani Will Haley Taha Kass-Hout Kyle Hernandez Michael Ingram Hara Prasad Juvvala Gina Kuffel Plamen Martinov J Montgomery Maxwell John McCann Ankit Malhotra Noah Metoki-Shlubsky Chris Meyer Andre Paredes Jawad Qureshi Xenia Ritter Philip Schumm Mingfei Shao Urvi Sheth Trevar Simmons Alexander VanTol Zhenyu Zhang Robert L Grossman 《J Am Med Inform Assoc》2022,29(4):619
ObjectiveThe objective was to develop and operate a cloud-based federated system for managing, analyzing, and sharing patient data for research purposes, while allowing each resource sharing patient data to operate their component based upon their own governance rules. The federated system is called the Biomedical Research Hub (BRH).Materials and MethodsThe BRH is a cloud-based federated system built over a core set of software services called framework services. BRH framework services include authentication and authorization, services for generating and assessing findable, accessible, interoperable, and reusable (FAIR) data, and services for importing and exporting bulk clinical data. The BRH includes data resources providing data operated by different entities and workspaces that can access and analyze data from one or more of the data resources in the BRH.ResultsThe BRH contains multiple data commons that in aggregate provide access to over 6 PB of research data from over 400 000 research participants.Discussion and conclusionWith the growing acceptance of using public cloud computing platforms for biomedical research, and the growing use of opaque persistent digital identifiers for datasets, data objects, and other entities, there is now a foundation for systems that federate data from multiple independently operated data resources that expose FAIR application programming interfaces, each using a separate data model. Applications can be built that access data from one or more of the data resources. 相似文献
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Kellie M Walters Anna Jojic Emily R Pfaff Marie Rape Donald C Spencer Nicholas J Shaheen Brent Lamm Timothy S Carey 《J Am Med Inform Assoc》2022,29(4):707
Institutions must decide how to manage the use of clinical data to support research while ensuring appropriate protections are in place. Questions about data use and sharing often go beyond what the Health Insurance Portability and Accountability Act of 1996 (HIPAA) considers. In this article, we describe our institution’s governance model and approach. Common questions we consider include (1) Is a request limited to the minimum data necessary to carry the research forward? (2) What plans are there for sharing data externally?, and (3) What impact will the proposed use of data have on patients and the institution? In 2020, 302 of the 319 requests reviewed were approved. The majority of requests were approved in less than 2 weeks, with few or no stipulations. For the remaining requests, the governance committee works with researchers to find solutions to meet their needs while also addressing our collective goal of protecting patients. 相似文献