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Feasibility of creating a National ALS Registry using administrativedata in the United States

机译:使用行政部门创建国家ALS注册中心的可行性美国的数据

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摘要

Uncertainty about the incidence and prevalence of amyotrophic lateral sclerosis (ALS), as well as the role of the environment in the etiology of ALS, supports the need for a surveillance system/registry for this disease. Our aim was to evaluate the feasibility of using existing administrative data to identify cases of ALS. The Agency for Toxic Substances and Disease Registry (ATSDR) funded four pilot projects at tertiary care facilities for ALS, HMOs, and state based organizations. Data from Medicare, Medicaid, the Veterans Health Administration, and Veterans Benefits Administration were matched to data available from site-specific administrative and clinical databases for a five-year time-period (1 January 2001–31 December 2005). Review of information in the medical records by a neurologist was considered the gold standard for determining an ALS case. We developed an algorithm using variables from the administrative data that identified true cases of ALS (verified by a neurologist). Individuals could be categorized into ALS, possible ALS, and not ALS. The best algorithm had sensitivity of 87% and specificity of 85%. We concluded that administrative data can be used to develop a surveillance system/ registry for ALS. These methods can be explored forcreating surveillance systems for other neurodegenerative diseases.
机译:关于肌萎缩性侧索硬化症(ALS)的发生率和患病率的不确定性以及环境在ALS病因中的作用,都支持对该疾病的监测系统/注册表的需求。我们的目标是评估使用现有管理数据来识别ALS案例的可行性。有毒物质和疾病登记局(ATSDR)在ALS,HMO和州级组织的三级医疗机构资助了四个试点项目。来自Medicare,Medicaid,退伍军人卫生管理局和Veterans Benefits Administration的数据与特定地点的行政和临床数据库中的数据进行了为期五年(2001年1月1日至2005年12月31日)的匹配。神经科医生对病历中信息的审查被认为是确定ALS病例的金标准。我们使用管理数据中的变量开发了一种算法,该算法可识别ALS的真实病例(由神经科医生验证)。可以将个人分类为ALS,可能的ALS,而不是ALS。最佳算法的灵敏度为87%,特异性为85%。我们得出的结论是,可以使用管理数据来开发ALS的监视系统/注册表。这些方法可以探索建立其他神经退行性疾病的监测系统。

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