Clinical trial · Interventional
Clinical Evaluation of AI Decision Support for Early Rehabilitation After Surgery
Evaluation of Clinical Effectiveness and Implementation of an Artificial Intelligence Based Decision Support Tool That Guides Early Rehabilitation After Gastrointestinal and Oncology Surgery
- Source
- ClinicalTrials.gov
- Retrieved
- Sep 8, 2026
- Layer
- normalized (units and labels harmonized; values unchanged)
- Run
- ING-CLINICALTRIALS-20260908-000001
Summary
Brief summary (as posted)
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.
Conditions
Conditions (2)
Free-text conditions as registered, with the CancerIndex entity they were reconciled to and the match type.
| Condition (as posted) | Mapped entity | Match | Confidence |
|---|---|---|---|
| Gastrointestinal Cancers | Malignant Digestive System Neoplasm | ALIAS | 0.90 |
| Oncologic Surgery | — | UNRESOLVED | — |
Interventions
Interventions (1)
| Intervention | Type | Mapped drug | Match |
|---|---|---|---|
| DESIRE: AI-Based Clinical Decision Support for Postoperative Rehabilitation Planning | Device | — | UNRESOLVED |
Design
Arms and outcomes
Arms (1)
- type
- EXPERIMENTAL
- label
- Cohort of 103 patients undergoing GE/oncological surgery and admitted >2 days after surgery
- interventionNames
- Device: DESIRE: AI-Based Clinical Decision Support for Postoperative Rehabilitation Planning
Primary outcomes (1)
- measure
- Proportion of patients requiring unplanned escalation of hospital-specific care within 30 days after early transfer to rehabilitation area.
- timeFrame
- From postoperative day 2 (time of AI prediction and potential transfer to rehabilitation area) through 30 days after surgery
- description
- 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
Eligibility
Eligibility (as posted)
- Sex
- All
- Minimum age
- 18 Years
Show eligibility criteria text
Inclusion Criteria: * 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 Exclusion Criteria: * 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
References
Publications (0)
Data not yet available