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
Overview
- Phase
- Not Applicable
- Intervention
- Not specified
- Conditions
- Artificial Intelligence
- Sponsor
- University Ghent
- Enrollment
- 69
- Locations
- 3
- Primary Endpoint
- Identify subdomains of the antimicrobial stewardship cycle with potential for AI/Big data application
- Status
- Completed
- Last Updated
- 3 years ago
Overview
Brief Summary
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.
Investigators
Eligibility Criteria
Inclusion Criteria
- •Medical specialist or specialist in training working in intensive care at the time of the study.
Exclusion Criteria
- •Age \< 18 yo
Outcomes
Primary Outcomes
Identify subdomains of the antimicrobial stewardship cycle with potential for AI/Big data application
Time Frame: 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.
Time Frame: 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.
Time Frame: 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
Time Frame: 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).
Secondary Outcomes
- 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)