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利用医疗保健数据库进行药物流行病学研究。

Utilization of health care databases for pharmacoepidemiology.

机构信息

Division of Genomic Epidemiology and Clinical Trials, Advanced Medical Research Center, Nihon University School of Medicine, 30-1 Oyaguchi-Kamimachi, Itabashi-ku, Tokyo 173-8610, Japan.

出版信息

Eur J Clin Pharmacol. 2012 Feb;68(2):123-9. doi: 10.1007/s00228-011-1088-2. Epub 2011 Aug 2.

Abstract

Pharmacoepidemiology is the study of the utilization and effects of drugs in clinical and population settings, and the outcomes of drug therapy. The growing trend of recording computerized data that will increasingly be automated into health care delivery is making the use of large datasets more and more common in pharmacoepidemiologic research. Most retrospective databases offer large populations and longer observation periods with real-world practice and can answer a variety of research questions quickly and cost-effectively. Observational studies, specifically using large databases, can complement findings from randomized clinical trials (RCTs) by assessing treatment effectiveness in patients encountered in daily clinical practice, although they are more exposed to bias and certainly are lower on the hierarchy of evidence than RCTs. Furthermore, careful defining of the research question with appropriate design and application of advanced statistical techniques, e.g., propensity-score analysis or marginal structural models, can yield findings with validity and improve causal inference of treatment effects. Some existing guidelines for comparative effectiveness help decision makers to evaluate the quality of observational studies comparing the effectiveness of various medical products and services. Thus, the trend for utilization of databases for pharmacoepidemiology will continue to grow in coming years.

摘要

药物流行病学是在临床和人群环境中研究药物的使用和效果,以及药物治疗的结果。记录计算机数据的趋势不断增长,并且越来越多地将其自动化到医疗保健服务中,这使得在药物流行病学研究中越来越多地使用大型数据集。大多数回顾性数据库提供了大量人群和更长的观察期,具有真实世界的实践,可以快速且具有成本效益地回答各种研究问题。观察性研究,特别是使用大型数据库,可以通过评估在日常临床实践中遇到的患者的治疗效果来补充随机临床试验 (RCT) 的发现,尽管它们更容易受到偏差的影响,并且在证据层次上肯定低于 RCT。此外,通过适当的设计和应用先进的统计技术(例如倾向评分分析或边缘结构模型)仔细定义研究问题,可以得出具有有效性的结果,并提高对治疗效果的因果推断。一些现有的比较效果指南有助于决策者评估比较各种医疗产品和服务的有效性的观察性研究的质量。因此,未来几年,数据库在药物流行病学中的应用趋势将继续增长。

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