Development of a core data set for describing, measuring and reporting the learning curve in studies of novel invasive procedures: study protocol

Author:

Ramirez JozelORCID,Hoffmann ChristinORCID,Corrigan Neil,Kobetic Matthew,Macefield RhiannonORCID,Elliott DaisyORCID,Blazeby JaneORCID,Potter ShelleyORCID,Stocken Deborah D,Avery KerryORCID,Blencowe Natalie SORCID

Abstract

IntroductionThe introduction of novel surgical techniques and procedures remains poorly regulated and standardised. Although the learning curve associated with invasive procedures is a critical part of innovation, it is currently inconsistently defined, measured and reported. This study aims to develop a core data set that can be applied in all studies describing or measuring the learning curve in novel invasive procedures.MethodsA core data set will be developed using methods adapted from the Core Outcome Measures in Effectiveness Trials initiative. The study will involve three phases: (1) Identification of a comprehensive list of data items through (a) an umbrella review of existing systematic reviews on the learning curve in surgery and (b) qualitative interviews with key stakeholders. (2) Key stakeholders (eg, clinical innovators, clinicians, patients, methodologists, statisticians, journal editors and governance representatives) will complete a Delphi survey to score the importance of each data item, generating a shortened list. (3) Consensus meeting(s) with stakeholders to discuss and agree on the final core data set.Ethics and disseminationThe study is approved by an Institutional Ethics Committee at the University of Bristol (ref: 111362). Participants will complete written informed consent to participate. Dissemination strategies include scientific meeting presentations, peer-reviewed journal publications, patient engagement events, use of social media platforms, workshops and other events.

Funder

NIHR Bristol Biomedical Research Centre

Medical Research Council

Publisher

BMJ

同舟云学术

1.学者识别学者识别

2.学术分析学术分析

3.人才评估人才评估

"同舟云学术"是以全球学者为主线,采集、加工和组织学术论文而形成的新型学术文献查询和分析系统,可以对全球学者进行文献检索和人才价值评估。用户可以通过关注某些学科领域的顶尖人物而持续追踪该领域的学科进展和研究前沿。经过近期的数据扩容,当前同舟云学术共收录了国内外主流学术期刊6万余种,收集的期刊论文及会议论文总量共计约1.5亿篇,并以每天添加12000余篇中外论文的速度递增。我们也可以为用户提供个性化、定制化的学者数据。欢迎来电咨询!咨询电话:010-8811{复制后删除}0370

www.globalauthorid.com

TOP

Copyright © 2019-2024 北京同舟云网络信息技术有限公司
京公网安备11010802033243号  京ICP备18003416号-3