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利用电子药房报销数据中的供应天数值来评估骨质疏松症药物治疗的依从性被低估了。

Adherence to osteoporosis pharmacotherapy is underestimated using days supply values in electronic pharmacy claims data.

作者信息

Burden Andrea M, Paterson J Michael, Gruneir Andrea, Cadarette Suzanne M

机构信息

Leslie Dan Faculty of Pharmacy, University of Toronto, Toronto, ON, Canada.

出版信息

Pharmacoepidemiol Drug Saf. 2015 Jan;24(1):67-74. doi: 10.1002/pds.3718. Epub 2014 Oct 21.

Abstract

PURPOSE

Days supply (prescription duration) values are commonly used to estimate drug exposure and quantify adherence to therapy, yet accuracy is not routinely assessed, and potential inaccurate reporting has been previously identified. We examined the impact of cleaning days supply values on the measurement of adherence to oral bisphosphonates.

METHODS

We identified new users of oral bisphosphonates among Ontario seniors (April 2001-March 2011). Days supply values were examined by dose, and we identified misclassification by comparing observed values to dose-specific expected values. Days supply values not matching expected values were cleaned using dose-specific algorithms. One-year adherence to therapy was defined using measures of compliance (mean proportion of days covered [PDC], and categorized into high [PDC ≥ 80%], medium [50% < PDC < 80%], low [PDC ≤ 50%]) and persistence (30-day permissible gap). Estimates were compared using the observed and cleaned days supply values, stratified by site of patient residence (community or long-term care [LTC]).

RESULTS

We identified 337 729 (5% LTC) eligible new users. Among LTC patients, adherence estimates increased significantly following data cleaning: mean PDC (59 to 83%), proportion with high compliance (47 to 76%), and proportion persisting with therapy (62 to 78%). Modest increases were identified among community-dwelling patients following data cleaning (mean PDC, 71 to 74%; high compliance, 54 to 58%; and persistence, 56 to 61%).

CONCLUSIONS

Data cleaning to correct for exposure misclassification can influence estimates of adherence with oral bisphosphonate therapy, particularly in LTC. Results highlight the importance of developing data cleaning strategies to correct for exposure misclassification and improve transparency in pharmacoepidemiologic studies.

摘要

目的

日剂量供应(处方持续时间)值通常用于估计药物暴露量并量化治疗依从性,但准确性并非常规评估内容,且此前已发现存在潜在的不准确报告情况。我们研究了清理日剂量供应值对口服双膦酸盐类药物依从性测量的影响。

方法

我们在安大略省老年人中确定了口服双膦酸盐类药物的新使用者(2001年4月至2011年3月)。按剂量检查日剂量供应值,并通过将观察值与特定剂量的预期值进行比较来确定错误分类。不匹配预期值的日剂量供应值使用特定剂量算法进行清理。使用依从性测量指标(平均覆盖天数比例[PDC])定义一年的治疗依从性,并分为高依从性(PDC≥80%)、中等依从性(50%<PDC<80%)、低依从性(PDC≤50%),以及持续性(30天允许间隔)。使用观察到的和清理后的日剂量供应值进行估计比较,按患者居住地点(社区或长期护理[LTC])分层。

结果

我们确定了337729名符合条件的新使用者(5%为长期护理患者)。在长期护理患者中,数据清理后依从性估计值显著增加:平均PDC(从59%增至83%)、高依从性比例(从47%增至76%)以及持续接受治疗的比例(从62%增至78%)。数据清理后,社区居住患者的依从性有适度增加(平均PDC,从71%增至74%;高依从性,从54%增至58%;持续性,从56%增至61%)。

结论

为纠正暴露错误分类而进行的数据清理会影响口服双膦酸盐类药物治疗依从性的估计,尤其是在长期护理患者中。结果凸显了制定数据清理策略以纠正暴露错误分类并提高药物流行病学研究透明度的重要性。

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