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首页> 外文期刊>BMC Medical Informatics and Decision Making >From prescription drug purchases to drug use periods – a second generation method (PRE2DUP)
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From prescription drug purchases to drug use periods – a second generation method (PRE2DUP)

机译：从处方药购买到药物使用期–第二代方法（PRE2DUP）

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Background Databases of prescription drug purchases are now widely used in pharmacoepidemiologic studies. Several methods have been used to generate drug use periods from drug purchases to investigate various aspects; e.g., to study associations between exposure and outcome. Typically, such methods have been fairly simplistic, with fixed assumptions of drug use pattern and or dose (for example, the assumed usage of 1 tablet per day). This paper describes a novel PRE2DUP method that constructs drug use periods from purchase histories, and verified by a validation based on an expert evaluation of the drug use periods generated by the method. Methods The PRE2DUP method is a novel approach based on mathematical modelling of personal drug purchasing behaviors. The method uses a decision procedure that includes each person’s purchase history for each ATC code, processed in a chronological order. The method constructs exposure time periods and estimates the dose used during the period by considering the purchased amount in Defined Daily Doses (DDDs), which is recorded in the prescription register database. This method takes account of stockpiling of drugs, personal purchasing pattern; i.e., regularity of the purchases, and periods of hospital or nursing home care where drug use is not recorded in the prescription register. The method can be applied to a variety of drug classes with different doses and use patterns by controlling restriction parameters for each ATC class, or even each drug package. In the presented example, the PRE2DUP method was applied to a register-based MEDALZ-2005 study cohort. All drug purchases (3,793,085) recorded in the Finnish prescription register between 2002 and 2009 for persons with Alzheimer’s disease (28,093) were included. Results Results of the expert-opinion based validation indicate that PRE2DUP method creates drug use periods with a relatively high correctness. Drugs with varying patterns of use and drugs used on a short-term basis only require more precise parameters. Conclusions PRE2DUP method gives highly accurate drug use periods for most drug classes, especially those meant for long-term use.
机译：背景技术处方药购买数据库现在已广泛用于药物流行病学研究。已经使用几种方法从毒品购买中产生毒品使用期限，以调查各个方面。例如，研究暴露与结果之间的关联。通常，在固定使用药物模式和/或剂量的前提下（例如，假设每天使用1片），这种方法非常简单。本文介绍了一种新颖的PRE2DUP方法，该方法可根据购买历史记录构造药物使用期限，并通过对该方法产生的药物使用期限的专家评估，通过验证进行验证。方法PRE2DUP方法是一种基于对个人药品购买行为进行数学建模的新颖方法。该方法使用一种决策程序，其中包括每个人按时间顺序处理的每个ATC代码的购买历史记录。该方法构建暴露时间段，并通过考虑定义的每日剂量（DDD）中的购买量来估算该时间段内使用的剂量，该剂量记录在处方记录数据库中。这种方法考虑了药品库存，个人购买方式;即购买的规律性，以及处方记录中未记录药物使用情况的医院或疗养院的护理期限。通过控制每个ATC类甚至每个药物包装的限制参数，该方法可以应用于具有不同剂量和使用方式的各种药物类别。在给出的示例中，PRE2DUP方法应用于基于寄存器的MEDALZ-2005研究队列。在2002年至2009年之间，芬兰处方药记录中记录的所有针对阿尔茨海默氏病患者的购买药品（3,793,085）（28,093）都包括在内。结果基于专家意见的验证结果表明，PRE2DUP方法创建的药物使用期具有较高的正确性。具有不同使用模式的药物和短期使用的药物仅需要更精确的参数。结论PRE2DUP方法可为大多数药物类别（尤其是那些需要长期使用的药物）提供高度准确的药物使用期限。

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