...
首页> 外文期刊>BMC Medical Research Methodology >Clinical researchers’ lived experiences with data quality monitoring in clinical trials: a qualitative study
【24h】

Clinical researchers’ lived experiences with data quality monitoring in clinical trials: a qualitative study

机译:临床研究人员在临床试验中存在数据质量监测的生活经验:定性研究

获取原文
           

摘要

Fundamental to the success of clinical research that involves human participants is the quality of the data that is generated. To ensure data quality, clinical trials must comply with the Good Clinical Practice guideline which recommends data monitoring. To date, the guideline is broad, requires technology for enforcement, follows strict industry standards, mostly designed for drug-registration trials and based on informal consensus. It is also unknown what challenges clinical trials and researchers face in implementing data monitoring procedures. Thus, this study aimed to describe researcher experiences with data quality monitoring in clinical trials. We conducted semi-structured telephone interviews following a guided-phenomenological approach. Participants were recruited from the Australian and New Zealand Clinical Trials Registry and were researchers affiliated with a listed clinical study. Each transcript was analysed with inductive thematic analysis before thematic categorisation of themes from all transcripts. Primary, secondary and subthemes were categorised according to the emerging relationships. Data saturation were reached after interviewing seven participants. Five primary themes, two secondary themes and 21 subthemes in relation to data quality monitoring emerged from the data. The five primary themes included: education and training, ways of working, working with technology, working with data, and working within regulatory requirements. The primary theme ‘education and training’ influenced the other four primary themes. While ‘working with technology’ influenced the ‘way of working’. All other themes had reciprocal relationships. There was no relationship reported between ‘working within regulatory requirements’ and ‘working with technology’. The researchers experienced challenges in meeting regulatory requirements, using technology and fostering working relationships for data quality monitoring. Clinical trials implemented a variety of data quality monitoring procedures tailored to their situation and study context. Standardised frameworks that are accessible to all types of clinical trials are needed with an emphasis on education and training.
机译:涉及人类参与者的临床研究成功的基础是产生的数据的质量。为确保数据质量,临床试验必须符合建议数据监测的良好临床实践指南。迄今为止,该指南广泛需要执行技术,遵循严格的行业标准,主要是为药物登记试验而设计,并以非正式的共识为设计。它还未知挑战临床试验和研究人员在实施数据监测程序方面的挑战。因此,本研究旨在描述临床试验中数据质量监测的研究人员经验。我们通过指导现象学方法进行半结构化电话访谈。与澳大利亚和新西兰临床试验登记处的招聘参与者,是隶属于上市临床研究的研究人员。通过在主题分类所有转录物的主题前进行归纳专题分析进行分析每个转录物。根据新出现的关系对初级,次要和次次进行分类。在采访七位参与者之后达到数据饱和度。五个主要主题,两个二级主题和21个副在数据中的数据质量监测相关。五个主要主题包括:教育和培训,工作方式,与技术合作,与数据一起工作,并在监管要求内工作。主要主题“教育和培训”影响了其他四个主要主题。虽然“使用技术”影响了“工作方式”。所有其他主题都有互惠关系。在“监管要求”和“与技术”之间的“工作”中没有任何关系。研究人员在满足监管要求,使用技术和培养工作关系进行数据质量监测,经历了挑战。临床试验实施了各种数据质量监测程序,对其情况和学习背景量身定制。需要所有类型的临床试验可访问的标准化框架,并强调教育和培训。

著录项

相似文献

  • 外文文献
  • 中文文献
  • 专利
获取原文

客服邮箱:kefu@zhangqiaokeyan.com

京公网安备:11010802029741号 ICP备案号:京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有
  • 客服微信

  • 服务号