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量化由于行政数据库中药物覆盖范围受限导致药物暴露分类错误的影响:一项模拟队列研究。

Quantifying the impact of drug exposure misclassification due to restrictive drug coverage in administrative databases: a simulation cohort study.

机构信息

School of Public Health, University of Alberta, Edmonton, AB, Canada.

出版信息

Value Health. 2012 Jan;15(1):191-7. doi: 10.1016/j.jval.2011.08.005. Epub 2011 Oct 19.

Abstract

OBJECTIVE

Drug exposure misclassification may occur in administrative databases when individuals obtain nonreimbursed drugs by paying "out-of-pocket" or via alternative drug coverage plans. We examined the apparent association between oral antidiabetic therapy and mortality by simulating the effects of restrictive drug coverage policies.

METHODS

Population-based cohort study of 12,272 new patients using oral antidiabetic agents were identified using the administrative databases of Saskatchewan Health, 1991 to 1996. We randomly misclassified 0% [base case], 10%, 25%, and 50% of known patients taking metformin according to either overt drug exposure (e.g., metformin users switched to nonusers) or time of metformin initiation (e.g., delayed capture of exposure); thereby simulating the use of a "non-formulary" or "special authorization" policy, respectively. We also simulated an age-dependent coverage policy, mimicking a policy restricted to seniors.

RESULTS

Metformin use was associated with lower mortality compared with sulfonylurea use in the base case (adjusted hazard ratio [aHR] 0.88, 95% confidence interval [CI] 0.78-0.99) and the nonformulary simulations. The special authorization simulations demonstrated, however, an increasing relative mortality hazard of metformin versus sulfonylurea exposure: aHR 0.96, 95% CI 0.96-0.97 and aHR 1.34, 95% CI 1.31-1.37, for 10% and 50% delays in coverage capture respectively when 50% of metformin users were misclassified. Age-dependent drug coverage had a variable impact on mortality risk compared with the base-case cohort; however, a new-user simulation with a 1-year washout revealed consistent results to the base-case analysis.

CONCLUSION

Restrictive drug coverage policies may result in substantial drug exposure misclassification, potentially severely biasing the results of drug-outcome relationships using administrative databases.

摘要

目的

当个人通过自付“现金”或通过替代药物覆盖计划获得无报销药物时,药物暴露分类错误可能会出现在行政数据库中。我们通过模拟限制药物覆盖政策的影响来研究口服抗糖尿病治疗与死亡率之间的明显关联。

方法

使用萨斯喀彻温省健康管理局的行政数据库,对 1991 年至 1996 年期间使用口服抗糖尿病药物的 12272 名新患者进行了基于人群的队列研究。我们随机错误分类了 0%(基础病例)、10%、25%和 50%已知服用二甲双胍的患者,根据明显的药物暴露情况(例如,二甲双胍使用者转换为非使用者)或二甲双胍开始使用的时间(例如,暴露时间延迟);从而分别模拟使用“非处方”或“特殊授权”政策。我们还模拟了一种年龄依赖性的覆盖政策,模拟仅限于老年人的政策。

结果

在基础病例(调整后的危害比[aHR]0.88,95%置信区间[CI]0.78-0.99)和非处方模拟中,与磺酰脲类药物相比,二甲双胍的使用与较低的死亡率相关。然而,特殊授权模拟显示,与磺酰脲类药物暴露相比,二甲双胍的相对死亡率风险逐渐增加:当 50%的二甲双胍使用者被错误分类时,分别延迟覆盖率捕获 10%和 50%时,aHR 为 0.96,95%CI 0.96-0.97 和 aHR 为 1.34,95%CI 1.31-1.37。与基础病例队列相比,年龄依赖性药物覆盖对死亡率风险有不同的影响;然而,使用 1 年洗脱期的新用户模拟得出的结果与基础病例分析一致。

结论

限制药物覆盖政策可能会导致大量药物暴露分类错误,这可能会严重偏倚使用行政数据库的药物结果关系的结果。

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