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A comparison of paper -based data submission to remote data capture for minimizing data entry errors in cancer clinical research.

机译:将纸质数据提交与远程数据捕获进行比较,以最大程度地减少癌症临床研究中的数据输入错误。

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摘要

Background. Patient data are essential for judging the safety and efficacy of cancer clinical trials. The current process of paper-based data entry provides opportunities for incurring data discrepancies. Automated systems have shown potential to reduce the number of data entry errors and preserve the quality of clinical trial data. To test this potential, this study examined case report forms (CRFs) to test for differences in the proportion of discrepancies and the time to resolve these discrepancies between a paper-based data entry and OracleRTM Clinical (OC) Remote Data Capture (RDC).;Objective. The purpose of this study was to examine differences in the proportion of errors and the time to resolve specific errors between a paper-based CRF and an electronic RDC format. Reason's conceptual framework for error detection and recovery feedback loop was used to guide this research where the warning environmental cueing function provided feedback to the end-user.;Results. The sample consisted of 445 RDC and 445 paper-based CRFs submitted to the Cancer Trial Support Unit (CTSU) from March 12, 2004 through March 28, 2005. There was a significant reduction in the proportion of overall data discrepancies for RDC as compared to paper-based CRFs (46.5% vs. 31.7%, p<.001). Similar results were found for univariate (58.6% vs. 41.2%, p<.001) and multivariate (64% vs. 36%, p<.001) discrepancies. Of the total sample of 890 CRFs analyzed for this study, 509 (57.2%) had no discrepancies. For the 381 (42.5%) forms with discrepancies there was no difference in the mean number of days to resolve discrepancies between RDC and paper-based (43 vs. 35). However, RDC had a greater proportion of resolved discrepancies (52% vs. 48%, p<.001).;Conclusion. The results from this study supported Reason's concept of error detection and recovery. RDC data entry format decreased overall, univariate and multivariate data discrepancies for patient information collected on a colon cancer study; however, there was no difference in the timeline for discrepancy resolution between the two formats. Further studies are recommended to test alternate definitions of discrepancy resolution time points. Results from this study can only be generalized to automated systems that use Oracle RTM Clinical and the instance configuration specific for the programmed edit checks used for the colon cancer study. (Abstract shortened by UMI.).
机译:背景。患者数据对于判断癌症临床试验的安全性和有效性至关重要。当前的基于纸张的数据输入过程为产生数据差异提供了机会。自动化系统已显示出减少数据输入错误次数并保持临床试验数据质量的潜力。为了测试这种潜力,本研究检查了病例报告表(CRF),以检验差异比例的差异以及解决基于纸质数据输入和OracleRTM Clinical(OC)远程数据捕获(RDC)之间的差异的时间。 ;目的。这项研究的目的是检查错误比例的差异以及解决纸质CRF和电子RDC格式之间的特定错误的时间。使用Reason的错误检测和恢复反馈回路的概念框架来指导本研究,其中警告环境提示功能向最终用户提供了反馈。该样本包括从2004年3月12日至2005年3月28日提交给癌症试验支持部门(CTSU)的445个RDC和445个基于纸张的CRF。与RDC相比,RDC的总体数据差异所占比例显着降低纸质CRF(46.5%比31.7%,p <.001)。单变量(58.6%vs. 41.2%,p <.001)和多变量(64%vs. 36%,p <.001)差异也发现了相似的结果。在本研究分析的890个CRF中,有509个(57.2%)没有差异。对于有差异的381个表格(42.5%),解决RDC和纸质表格之间的差异的平均天数没有差异(43比35)。但是,RDC的已解决差异比例较大(52%对48%,p <.001)。这项研究的结果支持了Reason的错误检测和恢复概念。 RDC数据输入格式减少了在结肠癌研究中收集的患者信息的整体,单变量和多变量数据差异;但是,两种格式之间差异解决的时间轴没有差异。建议进一步研究以测试差异解决时间点的替代定义。这项研究的结果只能推广到使用Oracle RTM Clinical的自动化系统以及针对结肠癌研究的程序化编辑检查所特有的实例配置。 (摘要由UMI缩短。)。

著录项

  • 作者

    Meadows, Beverly Jane.;

  • 作者单位

    University of Maryland, Baltimore.;

  • 授予单位 University of Maryland, Baltimore.;
  • 学科 Nursing.;Information science.;Health care management.
  • 学位 Ph.D.
  • 年度 2006
  • 页码 122 p.
  • 总页数 122
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类 地球物理学;
  • 关键词

  • 入库时间 2022-08-17 11:41:04

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