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使用行政数据进行系统性自身免疫性风湿病监测。

Surveillance of systemic autoimmune rheumatic diseases using administrative data.

机构信息

Division of Clinical Epidemiology, Research Institute of the McGill University Health Centre, 687 Pine Avenue West, V-Building, V2.09, Montreal, QC H3A 1A1, Canada.

出版信息

Rheumatol Int. 2011 Apr;31(4):549-54. doi: 10.1007/s00296-010-1591-2. Epub 2010 Jul 28.

Abstract

There is growing interest in developing tools and methods for the surveillance of chronic rheumatic diseases, using existing resources such as administrative health databases. To illustrate how this might work, we used population-based administrative data to estimate and compare the prevalence of systemic autoimmune rheumatic diseases (SARDs) across three Canadian provinces, assessing for regional differences and the effects of demographic factors. Cases of SARDs (systemic lupus erythematosus, scleroderma, primary Sjogren's, polymyositis/dermatomyositis) were ascertained from provincial physician billing and hospitalization data. We combined information from three case definitions, using hierarchical Bayesian latent class regression models that account for the imperfect nature of each case definition. Using methods that account for the imperfect nature of both billing and hospitalization databases, we estimated the over-all prevalence of SARDs to be approximately 2-3 cases per 1,000 residents. Stratified prevalence estimates suggested similar demographic trends across provinces (i.e. greater prevalence in females-versus-males, and in persons of older age). The prevalence in older females approached or exceeded 1 in 100, which may reflect the high burden of primary Sjogren's syndrome in this group. Adjusting for demographics, there was a greater prevalence in urban-versus-rural settings. In our work, prevalence estimates had good face validity and provided useful information about potential regional and demographic variations. Our results suggest that surveillance of some rheumatic diseases using administrative data may indeed be feasible. Our work highlights the usefulness of using multiple data sources, adjusting for the error in each.

摘要

人们越来越感兴趣的是开发工具和方法,以利用现有的行政健康数据库来监测慢性风湿性疾病。为了说明这是如何工作的,我们使用基于人群的行政数据来估计和比较三个加拿大省份的系统性自身免疫性风湿病(SARDs)的患病率,评估区域差异和人口因素的影响。SARDs(红斑狼疮、硬皮病、原发性干燥综合征、多发性肌炎/皮肌炎)的病例是从省级医生计费和住院数据中确定的。我们结合了三种病例定义的信息,使用分层贝叶斯潜在类别回归模型,该模型考虑了每种病例定义的不完美性质。使用同时考虑计费和住院数据库不完美性质的方法,我们估计 SARDs 的总体患病率约为每 1000 名居民中有 2-3 例。分层患病率估计表明,各省之间存在类似的人口统计学趋势(即女性与男性相比,以及年龄较大的人群中患病率更高)。老年女性的患病率接近或超过每 100 人中有 1 例,这可能反映了该人群原发性干燥综合征的高负担。在调整人口统计学因素后,城市与农村地区的患病率更高。在我们的工作中,患病率估计具有良好的表面有效性,并提供了有关潜在区域和人口统计学差异的有用信息。我们的结果表明,使用行政数据对某些风湿病进行监测确实是可行的。我们的工作强调了使用多个数据源的有用性,并对每个数据源的错误进行了调整。

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