Qualitative Research Among Physicians and Junior Doctors Into the Preconditions for Implementing a Clinical Decision Support System (CDSS) Based on Artificial Intelligence (AI) in the ICU
试验速览
- 阶段
- 不适用
- 状态
- 已完成
- 入组人数
- 69
- 试验地点
- 3
- 主要终点
- Identify subdomains of the antimicrobial stewardship cycle with potential for AI/Big data application
研究概览
简要总结
The goal of this study is to explore the different attitudes and preconditions of potential end-users (doctors & physicians in training) required to achieve successful clinical implementation of models based on artificial intelligence (i.e. both machine learning and knowledge-driven techniques) as clinical decision support software.
研究设计
- 研究类型
- Observational
- 观察模型
- Other
- 时间视角
- Prospective
入排标准
- 年龄范围
- 18 Years 至 —（Adult, Older Adult）
- 性别
- All
- 接受健康志愿者
- 是
入选标准
- •Medical specialist or specialist in training working in intensive care at the time of the study.
排除标准
- •Age < 18 yo
结局指标
主要结局
Identify subdomains of the antimicrobial stewardship cycle with potential for AI/Big data application
时间窗: through study completion, an average of 1 year
Identify subdomains of the antimicrobial stewardship cycle for which participants think AI/Big data might be of use through a group discussion/interview. Reporting: frequencies.
Identify perceived potential benefits and harms when applying AI in the antimicrobial stewardship cycle.
时间窗: through study completion, an average of 1 year
Identify perceived potential benefits and harms when applying AI in the antimicrobial stewardship cycle through a group discussion. Reporting: frequencies.
Identify prerequisites that need to be fulfilled when AI/Big data based clinical decision support systems are used bedside from the viewpoint of the participants.
时间窗: through study completion, an average of 1 year
Identify prerequisites that need to be fulfilled when AI/Big data based clinical decision support systems are used bedside and identify the most important ones for different aspects of the antimicrobial stewardship cycle from the viewpoint of the participants through a group discussion. Reporting: frequencies.
Baseline attitudes towards artificial intelligence and big data in medicine
时间窗: baseline
Baseline attitudes towards artificial intelligence and big data in medicine will be collected through an online survey where participants will score their agreement with certain statements on a 6-point likert scale (Possible choices: Strongly agree - Agree - Neutral - Disagree - Totally Disagree - Not applicable).
次要结局
- Subgroup analysis: age(through study completion, an average of 1 year)
- Subgroup analysis: gender(through study completion, an average of 1 year)
- Subgroup analysis: working environment (type of hospital, type of ICU)(through study completion, an average of 1 year)
- Subgroup analysis: working experience (basic training and clinical experience).(through study completion, an average of 1 year)