Department of Medicine, Ottawa Hospital Research Institute, University of Ottawa, Ottawa, Ontario K1Y 4E9, Canada.
J Clin Epidemiol. 2012 Feb;65(2):126-31. doi: 10.1016/j.jclinepi.2011.08.002. Epub 2011 Nov 9.
The provision of health care frequently creates digitized data--such as physician service claims, medication prescription records, and hospitalization abstracts--that can be used to conduct studies termed "administrative database research." While most guidelines for assessing the validity of observational studies apply to administrative database research, the unique data source and analytical opportunities for these studies create risks that can make them uninterpretable or bias their results.
Nonsystematic review.
The risks of uninterpretable or biased results can be minimized by; providing a robust description of the data tables used, focusing on both why and how they were created; measuring and reporting the accuracy of diagnostic and procedural codes used; distinguishing between clinical significance and statistical significance; properly accounting for any time-dependent nature of variables; and analyzing clustered data properly to explore its influence on study outcomes.
This article reviewed these five issues as they pertain to administrative database research to help maximize the utility of these studies for both readers and writers.
医疗保健的提供经常会产生数字化数据,例如医生服务索赔、药物处方记录和住院摘要,这些数据可用于进行所谓的“行政数据库研究”。虽然评估观察性研究有效性的大多数指南都适用于行政数据库研究,但这些研究独特的数据来源和分析机会会带来风险,从而使研究结果变得不可解释或产生偏差。
非系统性综述。
通过以下方式,可以最大限度地降低不可解释或有偏差结果的风险:提供对使用的数据表的详细描述,重点说明数据表的创建原因和创建方式;测量和报告使用的诊断和程序代码的准确性;区分临床意义和统计学意义;正确考虑变量的任何时间依赖性;以及正确分析聚类数据,以探究其对研究结果的影响。
本文综述了这五个与行政数据库研究相关的问题,以帮助读者和作者最大限度地利用这些研究。