Department of Clinical Pharmacy and Translational Sciences and the Center for Pediatric Pharmacokinetics and Therapeutics, College of Pharmacy, University of Tennessee Health Science Center, Memphis, TN, USA.
Department of Pediatric and UTHSC and Oakridge National Laboratory Center in Biomedical Informatics, College of Medicine, University of Tennessee Health Science Center, Memphis, TN, USA.
J Clin Pharmacol. 2018 Oct;58 Suppl 10:S86-S93. doi: 10.1002/jcph.1141.
The immense amount of electronic health data (pharmacy and administrative claims, electronic health records, and clinical registries) that is being generated every day in the care of patients has the potential to be leveraged for improving clinical decisions at the point of care, uncovering or validating drug efficacy and drug safety. The potential use of big data for improving safe and effective use of medications is especially important in children because of their low drug exposure relative to adults. Electronic health data is collected primarily for clinical or billing purposes and not for research purposes. The major steps involved in data acquisition, extraction, aggregation, analysis, modeling, and interpretation are discussed. It is important to understand the limitation of big data and utilize appropriate study design and statistical methods. Possible applications are presented along with specific examples of how big data has been used in drug research to find that blip on the radar screen that may give an efficacy or safety signal that can lead to further investigation.
每天在患者护理中产生的大量电子健康数据（药房和管理索赔、电子健康记录和临床登记）有可能被利用来改善护理点的临床决策，发现或验证药物疗效和药物安全性。在儿童中，由于相对于成年人而言，药物暴露水平较低，因此大数据在改善药物安全有效使用方面的潜在用途尤为重要。电子健康数据主要是为了临床或计费目的而收集的，而不是为了研究目的。本文讨论了数据采集、提取、聚合、分析、建模和解释的主要步骤。了解大数据的局限性并利用适当的研究设计和统计方法非常重要。本文还介绍了可能的应用，并提供了具体示例，说明大数据如何用于药物研究，以发现雷达屏幕上的那个小点，该小点可能会发出疗效或安全性信号，从而可以进行进一步的调查。
