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开发一套核心数据集,用于描述,测量和报告新型侵入性手术研究中的学习曲线:研究协议
Jozel Ramirez1,2, Christin Hoffmann3, Neil Corrigan4
1National Institute for Health and Care Research Bristol Biomedical Research Centre, Bristol Centre for Surgical Research, Bristol Medical School, Population Health Sciences, University of Bristol, Bristol, UK jozel.ramirez@bristol.ac.uk.
BMJ open
|July 26, 2024
概括
本研究开发了一套标准化的核心数据集,用于测量新手术过程中的学习曲线. 这旨在提高定义,测量和报告外科创新成果的一致性.
科学领域:
- 外科创新和患者安全.
- 医疗器械开发和评估.
背景情况:
- 新的外科手术技术需要对学习曲线进行一致的评估,以确保安全实施.
- 目前用于定义,测量和报告外科学习曲线的方法不一致,缺乏标准化.
研究的目的:
- 开发一套核心数据集,适用于所有关于新型侵入性手术学习曲线的研究.
- 为了标准化术术创新的学习曲线的定义,测量和报告.
主要方法:
- 一个三阶段的方法,从有效性试验的核心成果措施 (COMET) 倡议中改编.
- 第一个阶段:通过总体审查和利益相关者采访进行全面的数据项目识别.
- 第二阶段:与关键利益相关者进行Delphi调查,以确定数据项的优先级.
- 第三阶段:共识会议,最终确定核心数据集.
主要成果:
- 将建立一个基于共识的核心数据集,用于评估外科学习曲线.
- 该数据集将为研究和临床实践提供标准化的框架.
结论:
- 标准化学习曲线的测量对于安全有效地引入新型外科手术程序至关重要.
- 开发的核心数据集将提高外科创新研究的质量和可比性.
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