Association measures of claims-based algorithms for common chronic conditions were assessed using regularly collected data in Japan
Association measures of claims-based algorithms for common chronic conditions were assessed using regularly collected data in Japan
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DOI：
10.1016/j.jclinepi.2018.03.004
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发表时间：
2018-07-01
影响因子：
7.2
通讯作者：
Yamazaki, Tsutomu
中科院分区：
文献类型：
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作者：
Hara, Konan;Tomio, Jun;Yamazaki, Tsutomu
目标：尽管索赔数据广泛用于医学研究，但其识别个人健康相关状况的能力尚未得到充分证明。我们使用年度健康筛查结果作为金标准，评估了基于索赔的算法（cba）在大量人群中识别常见慢性病患者的有效性。研究设计和设置：使用纵向索赔数据库（n = 523267）结合年度健康筛查结果，我们将健康筛查结果作为金标准来定义患有高血压、糖尿病和/或血脂异常的人群，并将其与各种cba进行比较。结果：采用基于诊断和用药代码的cba，对高血压的敏感性和特异性分别为74.5%（95%可信区间[CI]， 74.2% ~ 74.8%）和98.2%(98.2% ~ 98.3%)，对糖尿病的敏感性和特异性分别为78.6%（77.3% ~ 79.8%）和99.6%(99.5% ~ 99.6%)，对血脂异常的敏感性和特异性分别为34.5%（34.2% ~ 34.7%）和97.2%（97.2% ~ 97.3%）。当我们使用相同的cba而不局限于初级保健机构时，高血压（65.2% [95% CI, 64.9%-65.5%]）和糖尿病（73.0%[71.7%-74.2%]）的敏感性并未显著降低。结论：我们采用定期收集的数据，获得了适用于广泛人群的CBA关联测度。我们的框架可以作为cba有效性评估的基础，通过定期收集的数据来确定个人的健康状况。(C) 2018爱思唯尔公司版权所有。
Objectives: Although claims data are widely used in medical research, their ability to identify persons' health-related conditions has not been fully justified. We assessed the validity of claims-based algorithms (CBAs) for identifying people with common chronic conditions in a large population using annual health screening results as the gold standard.Study Design and Setting: Using a longitudinal claims database (n = 523,267) combined with annual health screening results, we defined the people with hypertension, diabetes, and/or dyslipidemia by applying health screening results as their gold standard and compared them against various CBAs.Results: By using diagnostic and medication code -based CBAs, sensitivity and specificity were 74.5% (95% confidence interval [CI], 74.2%-74.8%) and 98.2% (98.2%-98.3%) for hypertension, 78.6% (77.3%-79.8%) and 99.6% (99.5%-99.6%) for diabetes, and 34.5% (34.2%-34.7%) and 97.2% (97.2%-97.3%) for dyslipidemia, respectively. Sensitivity did not decrease substantially for hypertension (65.2% [95% CI, 64.9%-65.5%]) and diabetes (73.0% [71.7%-74.2%]) when we used the same CBAs without limiting to primary care settings.Conclusion: We used regularly collected data to obtain CBA association measures, which are applicable to a wide range of populations. Our framework can be a basis of the validity assessment of CBAs for identifying persons' health-related conditions with regularly collected data. (C) 2018 Elsevier Inc. All rights reserved.