Clinical Evaluation of AI Decision Support for Early Rehabilitation After Surgery
Trial statusNot yet recruiting
Trial phaseNot applicable
Trial typeInterventional
Biological sexAll
Age18+
SponsorErasmus Medical Center
About this trial
After gastrointestinal or oncology surgery, it can be difficult to determine when a patient is ready to safely begin early rehabilitation or move toward discharge. Delays may prolong hospital stay, while premature decisions may increase risks.
This study evaluates an artificial intelligence (AI)-based decision support tool that analyzes routinely collected hospital data to identify patients who are likely ready for early rehabilitation and discharge planning after surgery. The tool provides a simple yes/no output to support clinicians in their decision-making.
The AI tool does not replace clinical judgment. Treating physicians remain fully responsible for all care decisions.
The purpose of this study is to examine how well this tool performs in clinical practice and how it can be safely and effectively implemented to support postoperative care.
Eligibility criteria
This trial does not accept healthy volunteersQualifiers
Adults aged 18 years or older
Undergoing gastrointestinal or oncological surgery
Postoperatively admitted to the surgical ward
Expected to remain admitted for at least 2 days after surgery
Disqualifiers
Admitted to the intensive care unit (ICU) at the time of prediction on postoperative day 2
Inability to provide informed consent in Dutch or English
Trial design
Design model
Single group
Treatments tested in this trial
DESIRE: AI-Based Clinical Decision Support for Postoperative Rehabilitation Planning
DeviceThe intervention consists of the clinical use of a locked, non-adaptive artificial intelligence (AI)-based clinical decision support system (DESIRE) that analyzes routinely collected electronic health record data to predict, on postoperative day 2, the risk that a patient will require hospital-specific interventions after gastrointestinal or oncological surgery. The system automatically extracts demographic, perioperative, vital sign, laboratory, and medication-related variables and generates a binary (yes/no) output indicating whether the patient is likely to be at low risk for requiring additional hospital care. A predefined conservative threshold is used to identify patients eligible for early rehabilitation.
Treatment groups
103 Participants
are divided into 1 treatment groupGroup A: Cohort of 103 patients undergoing GE/oncological surgery and admitted >2 days after surgeryExperimental treatment 1 intervention
Trial outcomes
Primary outcomes
1
Proportion of patients requiring unplanned escalation of hospital-specific care within 30 days after early transfer to rehabilitation area.
This is a composite outcome, consisting of any of the following events: ICU admission Re-operation Radiological intervention Administration of intravenous antibiotics Respiratory failure (new need for supplemental oxygen) 30-day mortality 30-day emergency readmission
Time frame
From postoperative day 2 (time of AI prediction and potential transfer to rehabilitation area) through 30 days after surgerySponsors and contacts
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Source ClinicalTrials.gov
This trial is not recruiting at the moment. You can still explore other options: