Evaluation of Clinical Effectiveness and Implementation of an Artificial Intelligence Based Decision Support Tool That Guides Early Rehabilitation After Gastrointestinal and Oncology Surgery
Overview
- Phase
- Not Applicable
- Status
- Not yet recruiting
- Sponsor
- Erasmus Medical Center
- Enrollment
- 103
- Locations
- 1
- Primary Endpoint
- Proportion of patients requiring unplanned escalation of hospital-specific care within 30 days after early transfer to rehabilitation area.
Overview
Brief Summary
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.
Detailed Description
Patients who undergo gastrointestinal or oncology surgery often require careful monitoring after their operation. During the days following surgery, healthcare professionals assess many factors, such as vital signs, laboratory results, recovery progress, and the need for hospital-based treatments. Based on this information, decisions are made about when patients can safely start early rehabilitation or move toward discharge planning.
In this study, researchers are evaluating an artificial intelligence (AI)-based decision support tool designed to assist clinicians with these decisions. The tool analyzes routinely collected information from the electronic patient record, including demographic data, type of surgery, vital signs, laboratory values, and medication information. Using these data, the system provides a simple yes/no output indicating whether a patient is likely ready for early rehabilitation and discharge planning on the second day after surgery.
The AI tool is advisory only. It does not make treatment decisions and cannot initiate any actions. The treating physician always reviews the patient's condition independently and makes the final decision about care, rehabilitation, and discharge planning.
The study focuses on two main aspects:
- How accurately the AI tool identifies patients who are ready for early rehabilitation and discharge planning.
- How the tool can be safely and practically integrated into everyday clinical workflows.
Participation in this study does not change the standard of care. All patients continue to receive routine postoperative care according to existing hospital protocols. The AI tool serves solely as an additional source of information for clinicians.
Patient data used by the AI system are processed within secure hospital systems and handled in accordance with data protection regulations. No additional tests or procedures are required specifically for this study.
The results of this study may help improve postoperative care by supporting timely rehabilitation and discharge planning, potentially reducing unnecessary hospital stays while maintaining patient safety.
Study Design
- Study Type
- Interventional
- Allocation
- Na
- Intervention Model
- Single Group
- Primary Purpose
- Diagnostic
- Masking
- None
Eligibility Criteria
- Ages
- 18 Years to — (Adult, Older Adult)
- Sex
- All
- Accepts Healthy Volunteers
- No
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
Arms & Interventions
Cohort of 103 patients undergoing GE/oncological surgery and admitted >2 days after surgery
Intervention: DESIRE: AI-Based Clinical Decision Support for Postoperative Rehabilitation Planning (Device)
Outcomes
Primary Outcomes
Proportion of patients requiring unplanned escalation of hospital-specific care within 30 days after early transfer to rehabilitation area.
Time Frame: From postoperative day 2 (time of AI prediction and potential transfer to rehabilitation area) through 30 days after surgery
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
Secondary Outcomes
No secondary outcomes reported
Investigators
D.E. Hilling
Surgeon and Data Scientist
Erasmus Medical Center