Evaluation of Data Entry Errors and Data Changes to an Electronic Data Capture Clinical Trial Database.

Jules T Mitchel, Yong Joong Kim, Joonhyuk Choi, Glen Park, Silvana Cappi, David Horn, Morgan Kist, Ralph B D Agostino
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引用次数: 38

Abstract

Monitoring of clinical trials includes several disciplines, stakeholders, and skill sets. The aim of the present study was to identify database changes and data entry errors to an electronic data capture (EDC) clinical trial database, and to access the impact of the changes. To accomblish the aim, Target e*CRF was used as the EDC tool for a multinational, dose-finding, multicenter, double-blind, randomized, parallel, placebo-controlled trial to investigate efficacy and safety of a new treatment in men with lower urinary tract symptoms associated with benign prostatic hyperplasia. The main errors observed were simple transcription errors from the paper source documents to the EDC database. This observation was to be expected, since every transaction has an inherant error rate. What and how to monitor must be assessed within the risk-based monitoring section of the comprehensive data monitoring plan. With the advent of direct data entry, and the elimination of the requirement to transcribe from a paper source record to an EDC system, error rates should go down dramatically. In addition, protocol violations and data outside the normal range can be identified at the time of data entry and not days, weeks, and months after the fact.

电子数据采集临床试验数据库的数据输入错误和数据更改评估。
临床试验的监测包括几个学科、利益相关者和技能集。本研究的目的是确定电子数据采集(EDC)临床试验数据库的数据库更改和数据输入错误,并获取这些更改的影响。为了实现这一目标,Target e*CRF被用作EDC工具,用于一项多国、剂量发现、多中心、双盲、随机、平行、安慰剂对照试验,以研究一种新疗法对男性良性前列腺增生相关下尿路症状的疗效和安全性。观察到的主要错误是从纸质源文档到EDC数据库的简单转录错误。这种观察结果是意料之中的,因为每个事务都有一个固有的错误率。监测什么和如何监测必须在综合数据监测计划的基于风险的监测部分进行评估。随着直接数据输入的出现,以及从纸质源记录转录到EDC系统的需求的消除,错误率应该会显著下降。此外,可以在数据输入时识别协议违规和超出正常范围的数据,而不是在事实发生后的几天、几周和几个月。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
Drug Information Journal
Drug Information Journal 医学-卫生保健
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审稿时长
6-12 weeks
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