INDIANAPOLIS PATHOLOGY INFORMATICS NETWORK

描述：(申请人提供) 近三十年来，雷根斯特里夫研究所的研究人员一直在 成功捕获用于临床和研究的电子医疗信息 目的。他们一直是电子病历领域的领导者 标准。他们已经建立了一个可操作的、覆盖全市的医疗信息学 网络(由印第安纳波利斯？五大医院系统)。在基础上建设 这些已被证实的优势，我们建议创建一种“印第安纳波利斯病理学” 信息学网络“，用印第安纳州补充这五大系统？S 癌症登记处，老将S健康系统，和一个大的病理小组.这个 包括医院在内的医院约占全市的95%？S 住院和报告的癌症病例。这个基于人口的数据库 最初将提供大约150万份病理报告和4.5份 上百万块纸巾。这些数据将链接到医院实验室 结果、放射学报告、用药命令、出院摘要、诊断 代码，程序代码，相遇日期和所有癌症登记数据 参与的医院。我们所描述的分布式系统将基于 这些操作系统、数据库系统、编程语言和 软件(开放源码可用)将促进低成本和安全 国家实施。我们将考虑几种不同的查询方法 生成的数据库，构建了一个多层系统，该系统将分布 对每个SPR进行查询、对用户进行身份验证、取消身份识别并对所有 临床信息，并对整个过程进行审计。我们将与 著名的领先公司(A-Life)和NLP领域的专家 以便将病理报告自动编码到UMLS中。来自中国的病理学家 参与的六家医院都同意投入时间 协调活动并查看自动编码的数据流 他们各自的网站。出版的互联网领域的专家 通信、下一代互联网、患者身份识别 数据和安全问题将进一步确保这一宝贵的成功 项目。

DESCRIPTION: (provided by applicant) For almost three years decades, Regenstrief Institute investigators have successfully captured electronic medical information for clinical and research purposes. They have been leaders in the field of electronic medical record standards. They have built an operational, city-wide medical informatics network (consisting of Indianapolis? five major hospital systems). Building on these proven strengths, we propose to create an "Indianapolis Pathology Informatics Network", supplementing these five major systems with Indiana?s Cancer Registry, the Veteran?s Health system, and a large pathology group. The included hospitals account for roughly 95 percent of the city?s hospitalizations and reported cancer cases. This population-based database will initially provide access to roughly 1.5 million pathology reports and 4.5 million tissue blocks. These data will be linked to hospital laboratory results, radiology reports, medication orders, discharge summaries, diagnostic codes, procedure codes, dates of encounters, and cancer registry data from all participating hospitals. We will base our described distributed system on those operating systems, database systems, programming languages , and software (open-source as available) that will facilitate low-cost and secure national implementation. We will allow for several different query methods of the resultant database, building a multi-tier system that will distribute queries to each of the SPRs, authenticate users, de-identify and encrypt all clinical information, and audit the entire process. We will collaborate with a well-established leading company (A-Life) and an expert in the field of NLP in order to automatically code pathology reports into UMLS. Pathologists from each of the six participating hospitals have agreed to commit time to coordinating activities and reviewing automatically coded data streams from their respective sites. Published experts in the fields of Internet communication, the Next Generation Internet, de-identification of patient data, and security issues will further ensure the success of this valuable project.