Appropriate definition of diabetes using an administrative database: A cross-sectional cohort validation study.
Appropriate definition of diabetes using an administrative database: A cross-sectional cohort validation study.
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使用行政数据库对糖尿病的适当定义：横断面队列验证研究。
DOI：
10.1111/jdi.13641
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发表时间：
2022-03
影响因子：
3.2
通讯作者：
Takahashi Y
中科院分区：
文献类型：
--
作者：
Nishioka Y;Takeshita S;Kubo S;Myojin T;Noda T;Okada S;Ishii H;Imamura T;Takahashi Y
本研究的目的是量化糖尿病诊断中的错误，以供国家数据库使用，使用足够的人口规模。本验证研究中使用了由JMDC（日本东京）构建的索赔数据库，该数据库使用标准化疾病分类和匿名记录链接。我们在JMDC索赔数据库中纳入了2005年4月至2019年3月的健康保险索赔数据。我们排除了在日本没有特定健康检查记录的患者。样本量计算基于5%的糖尿病患病率和0.4%的绝对准确度（即，1，250，000个个体），以计算灵敏度、特异性、阳性预测值和阴性预测值。本研究共纳入2，999，152例患者，其中165，515例基于特定健康检查被归类为糖尿病患者（验证队列患病率为5.5%）。新设计的算法有三个元素-糖尿病的诊断相关代码，没有可疑标记，糖尿病的药物代码，然后这两个代码在同一记录上-并产生74.6%的灵敏度，阳性预测值为88.4%，Kappa指数为0.80（最高值）。在未来的索赔数据库研究中，我们验证的算法将作为糖尿病的诊断标准。算法9和12有三个元素：（i）没有可疑标记的糖尿病诊断相关代码;（ii）糖尿病药物代码;（iii）这两个代码在同一记录上。这些算法产生的诊断与基于特异性、阳性预测值和Kappa指数的特定健康检查的结果一致。在未来的索赔数据库研究中，这些经过验证的算法将作为糖尿病的诊断标准。
The purpose of the present study was to quantify errors in the diagnosis of diabetes for use in the national database, using a sufficient population size. A claims database constructed by the JMDC (Tokyo, Japan), using standardized disease classifications and anonymous record linkage, was used in this validation study. We included patients with health insurance claims data from April 2005 to March 2019 in the JMDC claims database. We excluded patients without a record of specific health checkups in Japan. Sample size calculation was based on a 5% prevalence of diabetes and 0.4% absolute accuracy (i.e., 1,250,000 individuals), to calculate the sensitivity, specificity, positive predictive value and negative predictive value. In total, 2,999,152 patients were included in this study, of which 165,515 were classified as having diabetes based on specific health checkups (validation cohort prevalence of 5.5%). The newly devised algorithm had three elements – the diagnosis‐related codes for diabetes without suspected flag, the medication codes for diabetes and then these two codes on the same record – and yielded a sensitivity of 74.6%, positive predictive value of 88.4% and Kappa Index of 0.80 (the highest values). In future claims database studies, our validated algorithms will be useful as diagnostic criteria for diabetes. Algorithms 9 and 12 had three elements: (i) the diagnosis‐related codes for diabetes without suspected flag; (ii) the medication codes for diabetes; and (iii) then these two codes on the same record. These algorithms yielded a diagnosis that agrees with the results of the specific health checkups based on specificity, positive predictive value and Kappa Index. In future claims database studies, these validated algorithms will be useful as diagnostic criteria for diabetes.
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影响因子：
4.1
作者：
Nishioka Y;Noda T;Okada S;Myojin T;Kubo S;Higashino T;Ishii H;Imamura T
通讯作者：
Imamura T
影响因子：
3.8
作者：
Blonde L;Khunti K;Harris SB;Meizinger C;Skolnik NS
通讯作者：
Skolnik NS
影响因子：
7.2
作者：
Hara, Konan;Tomio, Jun;Yamazaki, Tsutomu
通讯作者：
Yamazaki, Tsutomu
影响因子：
19.7
作者：
Kundel, HL;Polansky, M
通讯作者：
Polansky, M
影响因子：
5.1
作者：
Tanaka, Hirokazu;Sugiyama, Takehiro;Ohsugi, Mitsuru
通讯作者：
Ohsugi, Mitsuru