Enhancing Clinical Effectiveness Research with Natural Language Processing of EMR

描述（由申请人提供）：为了成功使用大型链接临床数据库进行比较有效性研究（CER），需要解决与分布式、异质性临床数据相关的一些关键信息学挑战。研究人员的电子网络是解决方案的一部分，因为它们可以弥合不同卫生系统的个人电子病历（EMR）造成的物理和组织鸿沟。此外，信息学研究已经证明了自动编码临床文本的可行性，增强了整合来自EMR的非结构化和非标准化临床数据的能力。通过这项研究，我们建议开发CER基础设施，广泛提供经验证的MediClass技术，用于对包含编码数据和文本临床记录的EMR进行自动分类，并证明该基础设施在6个不同卫生系统的哮喘和烟草使用患者人群中解决CER问题的潜力。哮喘和吸烟都给医疗保健系统带来了巨大的和可改变的负担，与哮喘和吸烟相关的多种疾病已被IOM和AHRQ作为通过比较有效性研究改善医疗保健系统的优先领域。我们建议开发，部署，操作和评估CER中心，一个基于互联网的平台进行CER，并证明其效用在研究哮喘和吸烟的临床干预措施。注册使用HUB的研究人员（从6家参与研究中心的研究团队开始）将能够使用安全网站配置和下载解决各自医疗保健组织内CER问题的MediClass应用程序，将这些IRB批准的处理数据集反馈给集中式数据协调中心，以便与其他医疗保健组织类似处理的数据合并，并使用汇集的数据库来回答大量真实世界人群的各种比较有效性问题。CER HUB的一项核心功能是（通过在线交互式工具）促进MediClass知识模块共享库的开发，这些模块提供EMR数据的统一标准化编码。这种共享的知识模块库可以让研究人员评估医疗保健多个领域的有效性，并访问否则锁定在文本临床笔记中的数据。CER HUB的目标是加速创建标准化知识，用于将异构EMR数据标准化为CER的临床事件表示。在项目期间，我们将利用这一基础设施进行2项研究，以解决6个参与卫生系统的哮喘患者和烟草使用者干预措施的有效性。作为一个持续的资源，该中心将提供一个合作开发平台，以加强潜在的任何医疗保健领域的比较有效性研究。 CER研究人员可以构建处理其EMR的软件应用程序，创建标准化数据集，允许CER使用安全网站配置和下载MediClass应用程序，以解决各自医疗保健组织内的CER问题，将这些IRB批准的处理后的数据集返回到集中式数据协调中心，以便与其他医疗保健组织类似处理的数据合并，并使用汇集的数据库来回答大量真实世界人群的各种比较有效性问题 公共卫生相关性：比较有效性研究（CER）要求临床数据采用标准格式，允许多个大型数据库有效组合，并要求对所有数据进行编码，以便可以自动汇总数据。然而，CER所需的大部分临床数据都在临床医生护理患者时撰写的文本临床笔记中。我们将建立一个集中的网站，CER研究人员可以构建软件应用程序，处理他们的电子病历，包括文本和编码数据，创建标准化的数据集，允许进行比较有效性研究。我们将通过在6个参与的卫生系统中进行CER研究，调查哮喘和吸烟干预措施的有效性，来证明这种基础设施的实用性。

DESCRIPTION (provided by applicant): To successfully use large linked clinical databases for comparative effectiveness research (CER) requires addressing some key informatics challenges associated with distributed, heterogeneous clinical data. Electronic networks of researchers are part of the solution because they can bridge the physical and organizational divides created by distinct health systems' individual electronic medical records (EMRs). In addition, informatics research has demonstrated the feasibility of automatically coding clinical text, enhancing the capacity to integrate both unstructured and non-standardized clinical data from EMRs. With this study, we propose to develop CER infrastructure, make broadly available the proven MediClass technology for automated classification of EMRs containing both coded data and text clinical notes, and demonstrate the potential of this infrastructure for addressing CER questions within the asthma and tobacco-using patient populations of 6 diverse health systems. Asthma and smoking each impose huge and modifiable burdens on the healthcare system, and multiple morbidities related to asthma and smoking have been targeted by the IOM and AHRQ as priority areas in efforts to improve the healthcare system through comparative effectiveness research. We propose to develop, deploy, operate and evaluate the CER HUB, an Internet-based platform for conducting CER, and to demonstrate its utility in studying clinical interventions in asthma and smoking. Researchers who register to use the HUB, beginning with the research team from the 6 participating study sites, will be able to use a secure website to configure and download MediClass applications addressing CER questions within their respective healthcare organizations, to contribute these IRB-approved, processed datasets back to a centralized data coordinating center to be pooled with data similarly processed from other healthcare organizations, and to use the pooled database to answer diverse comparative effectiveness questions of large, real-world populations. A central function of the CER HUB will be facilitating (through online, interactive tools) development of a shared library of MediClass knowledge modules that afford uniform, standardized coding of EMR data. This shared library of knowledge modules could permit researchers to assess effectiveness in multiple areas of healthcare and gain access to data otherwise locked away in text clinical notes. A goal of the CER HUB is to accelerate creation of standardized knowledge used to normalize heterogeneous EMR data as representations of clinical events for CER. During the project period we will conduct 2 studies using this infrastructure to address the effectiveness of interventions for asthmatics and tobacco users across the 6 participating health systems. As an ongoing resource, the HUB will provide a collaborative development platform for enhancing comparative effectiveness research in potentially any health care domain. CER researchers can build software applications that will process their EMRs, creating standardized datasets permitting CER using a secure website to configure and download MediClass applications addressing CER questions within their respective healthcare organizations, to contribute these IRB-approved, processed datasets back to a centralized data coordinating center to be pooled with data similarly processed from other healthcare organizations, and to use the pooled database to answer diverse comparative effectiveness questions of large, real-world populations PUBLIC HEALTH RELEVANCE: Comparative effectiveness research (CER) requires that clinical data be in standard forms allowing multiple, large databases to be efficiently combined, and requires that all of the data be coded so that automated summarization of the data is possible. However, much of the clinical data necessary for CER is in the text clinical notes written by clinicians when caring for patients. We will build a centralized website where CER researchers can build software applications that will process their electronic medical records, including both the text and coded data, creating standardized datasets permitting comparative effectiveness research. We will demonstrate the utility of this infrastructure by conducting CER studies investigating the effectiveness of interventions in asthma and smoking, across the 6 participating health systems.