INDIANAPOLIS PATHOLOGY INFORMATICS NETWORK

描述：（申请人提供） 近三十年来，Regenstrief研究所的研究人员 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，全市范围的医疗信息系统， 网络（包括印第安纳波利斯？五大医院系统）。基础上 这些已被证明的优势，我们建议创建一个“印第安纳波利斯病理学 Informatics Network”，以印第安纳州补充这五大系统？S 癌症登记处，退伍军人？卫生系统和一个大型病理学小组。的 包括医院约占全市的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450万份病理报告。 百万个组织块。这些数据将被链接到医院实验室 结果、放射学报告、药物医嘱、出院总结、诊断 代码，程序代码，遭遇日期和癌症登记数据， 参与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，以及 软件（如有开放源码），将有助于低成本和安全 国家执行。我们将允许几种不同的查询方法， 生成的数据库，构建一个多层系统， 查询每个SPR，验证用户，取消识别和加密所有 临床信息，并审核整个过程。我们将与A 知名的领先公司（A-Life）和NLP领域的专家， 以便将病理报告自动编码到UMLS中。病理学家来自 六家参与的医院都同意投入时间， 协调活动并审查自动编码的数据流， 各自的网站。互联网领域的专家 通信，下一代互联网，患者去身份化 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.