Identification of patients with systemic lupus erythematosus in administrative healthcare databases
Identification of patients with systemic lupus erythematosus in administrative healthcare databases
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DOI：
10.1177/0961203314543917
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发表时间：
2014-11-01
期刊：
影响因子：
2.6
通讯作者：
Skedgel, C.
中科院分区：
文献类型：
--
作者：
Hanly, J. G.;Thompson, K.;Skedgel, C.
目的验证和比较行政保健数据库中系统性红斑狼疮(SLE)患者识别的决策规则。方法采用100万全民医保人群的行政保健数据进行回顾性队列研究。在10年的时间里，可以获得关于医院出院和医生账单的信息。每个SLE病例按年龄和性别与随机选择的对照组进行4：1的匹配。结果我们确定了373例系统性红斑狼疮病例和1492例非系统性红斑狼疮对照病例，所有病例都经过了风湿科医生的审查。SLE病例定义的总体准确率在88.2-95.6%之间，kappa统计量在0.53-0.86之间。敏感性为41.0%~86.6%，特异性为92.4%~99.9%。在100万参考人群中，SLE的年平均发病率在29-255之间，平均年患病率在172-920之间。结论行政保健数据库中用于识别SLE患者的病例定义的准确性是可变的，当比较研究结果时应考虑这一点。这种可变性也可以在不同的研究设计中发挥优势，这取决于识别研究问题感兴趣的人群的灵敏度和特异度的相对重要性。
Objective Our aim was to validate and compare decision rules for the identification of patients with systemic lupus erythematosus (SLE) in administrative healthcare databases.Methods A retrospective cohort study was performed using administrative health care data from a population of 1 million people with access to universal healthcare. Information was available on hospital discharges and physician billings over a 10-year period. Each SLE case was matched 4:1 by age and gender to randomly selected controls. Seven case definitions were applied to identify SLE cases and their performance compared with the diagnosis by a rheumatologist.Results We identified 373 SLE cases and 1492 non-SLE controls, all of whom had been reviewed by a rheumatologist. The overall accuracy of the case definitions for SLE cases varied between 88.2-95.6% with a kappa statistic between 0.53-0.86. The sensitivity varied from 41.0-86.6% and the specificity between 92.4-99.9%. In a total reference population of 1 million the mean estimated annual incidence of SLE was between 29-255 and the mean estimated annual prevalence was between 172-920.Conclusion The accuracy of case definitions for the identification of SLE patients in administrative healthcare databases is variable and this should be considered when comparing results across studies. This variability may also be used to advantage in different study designs depending on the relative importance of sensitivity and specificity for identifying the population of interest to the research question.