经验教训:在一个大型城市研究机构开发COVID-19临床分期模型
Sean S Huang1, Lelia H Chaisson2,3, William Galanter1,4
1Department of Medicine, Division of Academic Internal Medicine and Geriatrics, University of Illinois Chicago, Chicago, IL, USA.
Journal of clinical and translational science
|May 30, 2023
概括
在COVID-19期间开发临床分期和预测模型提出了挑战. 这项研究反映了伊利诺伊大学芝加哥分校的障碍和经验教训.
科学领域:
- 医疗信息学 医疗信息学
- 临床研究 临床研究
- 流行病学 流行病学
背景情况:
- 在全球范围内,学术机构在COVID-19大流行期间开发了临床分期和预测模型.
- 利用了2019年7月至2022年3月间伊利诺伊大学芝加哥分校 (UIC) 的数据.
- 研究的旅程涉及成功和失败.
研究的目的:
- 讨论临床分期和预测模型的开发过程中遇到的障碍.
- 分享从研究过程中学到的经验教训.
- 反思发现的优点和缺点.
主要方法:
- 一个匿名的Qualtrics调查被分发给项目团队成员.
- 开放式问题侧重于项目目标,成功,失败以及需要改进的领域.
- 分析了调查答复,以确定关键主题.
主要成果:
- 在30名联系的团队成员中,有9人完成了匿名调查.
- 出现了四个主要主题:协作,基础设施,数据获取/验证和模型构建.
- 该研究确定了团队的优点和缺点.
结论:
- COVID-19研究工作为研究和数据翻译能力提供了宝贵的见解.
- 研究实践和数据翻译的持续改进正在进行中.
- 学到的经验教训将为未来的模型开发和研究计划提供信息.
关键词:
在 COVID-19 疫情中,学到的经验教训合作 合作 合作 合作数据采集数据采集数据基础设施的数据基础设施.数据验证数据的验证.信息系统信息系统信息系统预测模型的预测模型.翻译翻译翻译翻译翻译翻译更多相关视频
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