School of Public Health, University of Alberta, Edmonton, Alberta, Canada.
Clin Ther. 2012 Jun;34(6):1379-1386.e3. doi: 10.1016/j.clinthera.2012.04.009. Epub 2012 May 2.
Drugs reimbursed through a single-party payer such as health maintenance organizations or provincial governments are generally captured in administrative data if they have full-benefit status on that payer's formulary. However, drugs subject to restrictive drug coverage policies are often not fully captured if patients receive these drugs through mechanisms other than the single-payer formulary.
The goal of this study was to estimate the association between restrictive drug coverage and drug exposure misclassification across the Canadian provinces of Manitoba and Saskatchewan, which provide universal coverage for formulary-approved drugs to all citizens regardless of age or socioeconomic status.
Monthly dispensations were compared for 75 drugs between 2005 and 2008 from Canada's National Prescription Drug Utilization System database, which captures provincial drug formulary claims only, versus the IMS Brogan CompuScript Database, which captures all drug dispensations irrespective of formulary status. The association between restrictive drug coverage and drug exposure misclassification was measured using generalized estimating equations and multivariable adjustment.
On average, 84% of monthly retail drug dispensations were captured by provincial claims data: 100% of monthly dispensations were captured for drugs with full-benefit status but only 61% of dispensations for drugs with restrictive drug coverage (adjusted risk ratio = 0.65 [95% confidence interval, 0.56-0.75]). The direction and magnitude of the potential misclassification bias between full-benefit and restricted policy drugs were consistent across all drug classes examined: acid-reducing drugs (97% vs 66%), analgesics (89% vs 64%), central nervous system drugs (103% vs 61%), cardiovascular drugs (100% vs 57%), diabetes drugs (98% vs 61%), osteoporosis drugs (96% vs 57%), and respiratory drugs (112% vs 60%).
Drugs subject to restrictive coverage policies are substantially under-captured in administrative databases, leading to potential drug exposure misclassification in pharmacoepidemiologic studies relying on administrative databases. Pharmacoepidemiologic studies should clearly describe whether evaluated drugs are available as full benefits or subject to restrictive coverage policies and the potential impact on their results.
在单一付款方（如健康维护组织或省政府）下报销的药物，如果在该付款方的处方集上具有全福利状态，通常会在行政数据中捕获。然而，如果患者通过单一付款方处方集以外的机制获得这些药物，那么通常无法完全捕获受限制药物覆盖政策约束的药物。
本研究的目的是评估在提供处方批准药物全民覆盖的加拿大马尼托巴省和萨斯喀彻温省，限制药物覆盖与药物暴露错误分类之间的关联，无论年龄或社会经济地位如何。
比较了 2005 年至 2008 年期间来自加拿大国家处方药物利用系统数据库的 75 种药物的每月配药情况，该数据库仅捕获省级药物处方集的索赔，而 IMS Brogan CompuScript 数据库则捕获所有药物配药情况，无论处方集状态如何。使用广义估计方程和多变量调整来衡量限制药物覆盖与药物暴露错误分类之间的关联。
平均而言，84%的月度零售药物配药由省级索赔数据捕获：100%的月度配药由具有全福利状态的药物捕获，但仅 61%的具有限制药物覆盖的药物配药（调整后的风险比=0.65[95%置信区间，0.56-0.75]）。在所有检查的药物类别中，全福利和受限政策药物之间潜在的错误分类偏差的方向和程度是一致的：酸还原药物（97%对 66%）、镇痛药（89%对 64%）、中枢神经系统药物（103%对 61%）、心血管药物（100%对 57%）、糖尿病药物（98%对 61%）、骨质疏松症药物（96%对 57%）和呼吸药物（112%对 60%）。
受限制覆盖政策约束的药物在行政数据库中大量未被捕获，导致依赖行政数据库的药物流行病学研究中存在潜在的药物暴露错误分类。药物流行病学研究应明确描述评估药物是否作为全福利或受限制覆盖政策提供，以及对其结果的潜在影响。
