Automated Data Acquisition for Heart Failure: Performance Measures and Treatment

主要研究者：Jennifer Garvin博士 项目名称： 心力衰竭的自动数据采集：性能测量和治疗 对兽医保健的预期影响： 退伍军人管理局重新设计了其医疗保健系统，退伍军人健康管理局（VHA）， 包括更好地利用信息技术，衡量和报告业绩， 重组医疗保健服务和调整支付政策。但 通过回顾性图表审查收集用于质量测量的数据是耗时的， 贵了使用信息提取（IE）技术捕获质量测量数据 将有利于退伍军人的健康，并将改善退伍军人事务部的医疗保健服务。 项目背景：心力衰竭（HF）与高死亡率相关， 生活质量差。心力衰竭目前影响着近500万美国人， 自1970年以来，美国因这种情况而入院的人数增加了六倍（从 80，000每年超过500，000），部分原因是人口老龄化。心力衰竭也是 退伍军人医疗保健系统内治疗的退伍军人住院的头号原因。 由于电子健康记录的常规使用和IE的日益可用性， 技术，以自动化方式捕获性能测量数据的潜力 是一种现实的追求。 结论：本研究的目的是：a.使用信息提取技术， 确定并提取绩效治疗维度的必要要素 测量患有充血性心力衰竭的住院患者，B.将这些技术与现有的 手动抽象方法，以及c.检查性能偏差。 方法：这是一项描述性研究，将与联盟合作进行， 医疗保健信息学研究（CHIR）提供灵敏度，特异性， 和准确性的信息提取方法，以确定存在的性能 测量数据元素：评价左心室收缩功能，射血分数， 并为心衰住院患者提供合理的用药处方。使用的标准 确定存在的数据元素将与EPRP所需的元素相同。 这项研究将提供一个比较的准确性，现有的手工方法的数据 抽象使用自动化数据抽象的新方法，评估提供商对 这些新方法，并开发与VA性能和质量办公室合作， 其他成员团体传播研究结果。

Principal Investigator: Jennifer Garvin, PhD Project Title: Automated Data Acquisition for Heart Failure: Performance Measures and Treatment ANTICIPATED IMPACT ON VETERANS HEALTHCARE: The VA redesigned its health care system, the Veterans Health Administration (VHA), by including better use of information technology, measurement and reporting of performance, reorganization of health care delivery and realignment of payment policies. However, the collection of data for quality measures through retrospective chart review is time consuming and expensive. Using information extraction (IE) techniques to capture data for quality measurement would be beneficial to the health of veterans and would improve health care delivery in the VA. PROJECT BACKGROUND: There is an association of heart failure (HF) with high mortality and poor quality of life. Heart failure currently affects nearly 5 million Americans, and hospital admissions for this condition have increased six-fold in the United States since 1970 (from 80,000 per year to more than 500,000) due, in part, to an aging population. Heart failure is also the number one cause of hospitalizations of veterans treated within the VA health care system. Because of routine use of the electronic health record and the increasing availability of IE techniques, the potential of capturing the performance measurement data in an automated way is a realistic pursuit. OBJECTIVES: The objectives of the study are to: a. use information extraction techniques to identify and extract the required elements of the treatment dimension of the performance measure for inpatients with congestive heart failure, b. to compare these techniques to existing manual abstraction methods, and c. to examine performance deviations. METHODS: This is a descriptive study that will be undertaken in concert with the Consortium for Healthcare Informatics Research (CHIR) to provide accuracy measures of sensitivity, specificity, and accuracy of information extraction methodology to identify the presence of performance measurement data elements of: evaluation of left ventricular systolic function, ejection fraction, and appropriate medication prescription for inpatients with heart failure. The criteria used to determine the presence of the data elements will be the same as the EPRP required elements. This study will provide a comparison of the accuracy of the existing manual method of data abstraction with a new method of automated data abstraction, evaluate providers acceptance of these new methods, and develop collaborate with the VA Office of Performance and Quality and other constituent groups to disseminate the findings of the research.