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Data Quality and Medical Record Abstraction in the Veterans Health Administration's External Peer Review Program

机译：退伍军人健康管理局外部同行评审计划中的数据质量和医疗记录抽象

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Under the Veterans Health Administration's External Peer Review Program, the West Virginia Medical Institute (WVMI) conducts monthly medical record abstractions in over 150 VA Medical Centers throughout the United States and Puerto Rico. The abstractions are performed by approximately 90 highly trained abstractors and are used to assess VHA clinical performance for: in-patient and out-patient encounters, JCAHO ORYX measures, and ad hoc studies on topics such as management of low back pain, spinal chord injury, and diabetic foot care. To help improve the validity and reliability of the abstracted medical data, WVMI has implemented a multi-method approach to monitoring abstracted data quality. The approach includes five major components: 1. Bi-weekly computer-aided screening to detect anomalous performance (e.g., leading and terminal digit distributions of continuous variables); 2. On-site interrater reliability assessments and calculation of prevalence adjusted Kappa agreement between abstractors and supervising Network Coordinators; 3. Random and special assignment audits by one or more trained auditors; 4. Analyses using SAS Enterprise Miner (including runs and randomness testing, hierarchal modeling (decision tree and cluster analysis) and neural network programming for assessing performance; 5. Statistical process control for tracking and trending performance of abstractors, VAMCs, and items over time. In addition, WVMI has created web-enabled feedback capabilities so that key administrators can rapidly access and report on performance impacting data quality. This paper will outline the data quality techniques and results that have enhanced the use of medical record data for assessing clinical performance throughout the VHA system.
机译：根据退伍军人健康管理局的外部同行评审计划，西弗吉尼亚医学院（WVMI）在美国和波多黎各的150多个VA医疗中心进行每月病历抽象。该抽象由大约90次训练有素的摘要来进行，用于评估VHA临床表现：患者和门诊障碍，JCAHO ORYX措施，以及对低腰疼痛管理等主题的临时研究，脊柱弦损伤和糖尿病足部护理。为了帮助提高抽象的医疗数据的有效性和可靠性，WVMI已经实现了一种监控抽象数据质量的多方法方法。该方法包括五个主要组成部分：1。双每周计算机辅助筛查以检测异常性能（例如，连续变量的前导和终端数分布）; 2.现场Interrater可靠性评估和流行计算调整了摘录者和监督网络协调员的Kappa协议; 3.一个或多个培训的审计员随机和特殊分配审核; 4.使用SAS企业矿工（包括运行和随机性测试，层次建模（决策树和集群分析）和用于评估性能的神经网络编程（包括用于评估性能的神经网络编程; 5.统计过程控制摘录和培养者，VAMC和物品的表现随着时间的推移。此外，WVMI已创建支持网络的反馈功能，以便键管理员可以快速访问和报告影响数据质量的性能。本文将概述具有增强使用医疗记录数据的数据质量技术和结果，以评估临床表现。在整个VHA系统中。

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