Multi-centre validation and clinical experience of EzaPredictive for the Emergency Room and clinical departments
- Conditions
- verblijfsduur en/of opname van SEH patiënten en ligduur klinische patiëntennvt
- Registration Number
- NL-OMON53270
- Lead Sponsor
- Expertisecentrum Zorgalgoritmen
- Brief Summary
Not available
- Detailed Description
Not available
Recruitment & Eligibility
- Status
- Recruiting
- Sex
- Not specified
- Target Recruitment
- 250
Healthcare professionals in the participating hospitals, who
(1) are involved in patient flow management,
(2) work in an emergency department, acute admission department or inpatient
department during the study period and
(3) have received the necessary instruction beforehand
Healthcare professionals are excluded when it is not realistic to expect that
he/she will be able to make estimates for a minimum of 10 patients, given the
number of shifts he/she has scheduled during the study period.
Study & Design
- Study Type
- Observational non invasive
- Study Design
- Not specified
- Primary Outcome Measures
Name Time Method <p>The main study endpoints for the first objective (comparing predictions of ML<br /><br>and healthcare professionals) are the predictive performance of healthcare<br /><br>professionals and ML models.<br /><br><br /><br>The main study endpoints for the second objective (assessing healthcare<br /><br>professional experience of ML software) are the questionnaire outputs regarding<br /><br>healthcare professional experience with the EzaPredictive 1.0 software. </p><br>
- Secondary Outcome Measures
Name Time Method <p>The secondary study endpoints for the first objective (comparing predictions of<br /><br>ML and healthcare professionals) is the inter-rater reliability between<br /><br>healthcare professionals and ML models. </p><br>