Qualitative Research Among Physicians and Junior Doctors Into the Preconditions for Implementing a CDSS Based on AI in the ICU
- Conditions
- Artificial IntelligenceDecision Support Systems, ClinicalQualitative Research
- Registration Number
- NCT05303025
- Lead Sponsor
- University Ghent
- 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.
- Detailed Description
Not available
Recruitment & Eligibility
- Status
- COMPLETED
- Sex
- All
- Target Recruitment
- 69
- Medical specialist or specialist in training working in intensive care at the time of the study.
- Age < 18 yo
Study & Design
- Study Type
- OBSERVATIONAL
- Study Design
- Not specified
- Primary Outcome Measures
Name Time Method Identify subdomains of the antimicrobial stewardship cycle with potential for AI/Big data application 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. 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. 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 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 Outcome Measures
Name Time Method Subgroup analysis: age through study completion, an average of 1 year Explore if there are variations in the above mentioned outcomes when taking into account the age (years) of the participants.
Subgroup analysis: gender through study completion, an average of 1 year Explore if there are variations in the above mentioned outcomes when taking into account the gender of the participants.
Subgroup analysis: working environment (type of hospital, type of ICU) through study completion, an average of 1 year Explore if there are variations in the above mentioned outcomes when taking into account the working environment (University hospital vs non University hospital, small size hospital vs large size hospital, type of ICU (medical, surgery, mixed ICU, intermediate care)) - data which is collected in the baseline questionnaire) of the participants.
Subgroup analysis: working experience (basic training and clinical experience). through study completion, an average of 1 year Explore if there are variations in the above mentioned outcomes when taking into account the working experience (type of basic training (anesthesiology, internal medicine, surgery, other), clinical experience (years) - data which is collected in the baseline questionnaire) of the participants.
Trial Locations
- Locations (3)
OLV Aalst
🇧🇪Aalst, Belgium
ZNA Ziekenhuizen
🇧🇪Antwerpen, Belgium
Ghent University Hospital
🇧🇪Ghent, Belgium