Oncologic SurgeryDESIRENCT07406269
Clinical Evaluation of AI Decision Support for Early Rehabilitation After Surgery
A study testing DESIRE: AI-Based Clinical Decision Support for Postoperative Rehabilitation Planning in people with Oncologic Surgery and Gastrointestinal Cancers, run by Erasmus Medical Center at 1 site in Netherlands.
Trial 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. Read more about this study
- Who is it for?
- Ages 18 years and older
- Conditions the study is for
- Oncologic Surgery, Gastrointestinal Cancers
- What is being tested?
- DESIRE: AI-Based Clinical Decision Support for Postoperative Rehabilitation Planning
- Type of treatment
- Medical device
- Could I receive a placebo?
- No, everyone receives an active treatment
- How many people
- 103 participants
- Where
- 1 siteNetherlands
- Study dates
- 1 Jun 2026to 1 Jul 2027
- Phase
- Interventional
- Are there results?
- Not yet: the study is under way
Key requirements
Who can take part, as listed by the sponsor. Only the study team can confirm whether you are eligible, so take this list to your doctor.
- Ages 18 years and older
- All sexes
- No healthy volunteers
- Adult, Older adult
Who may be able to join
- 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
Who cannot join
- 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 locations and contacts
1 site in 1 country. Contact the study team or a site near you to ask about taking part.
Netherlands1 site
Erasmus MC, University Medical Center Rotterdam
Rotterdam
Denise Hilling, MD PhD, +31 10 704 19 02, d.hilling@erasmusmc.nl
About this study
Official title: Evaluation of Clinical Effectiveness and Implementation of an Artificial Intelligence Based Decision Support Tool That Guides Early Rehabilitation After Gastrointestinal and Oncology Surgery
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.
Read more
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.
Read the 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.
- Conditions
- Oncologic Surgery, Gastrointestinal Cancers
- Being tested
- DESIRE: AI-Based Clinical Decision Support for Postoperative Rehabilitation Planning
- Keywords
- Artificial Intelligence, Clinical Decision Support System, Postoperative Care, Early Rehabilitation, Gastrointestinal Surgery, Oncological Surgery, Predictive Modeling
- Medical subject headings
- Gastrointestinal Neoplasms
What participants receive
What participants receive. In a randomised study each person is assigned to one group by chance.
DESIRE: AI-Based Clinical Decision Support for Postoperative Rehabilitation PlanningDevice
The 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.
| Study group | Role | What they receive |
|---|---|---|
| Cohort of 103 patients undergoing GE/oncological surgery and admitted >2 days after surgery | Experimental | Not described Receives: Device: DESIRE: AI-Based Clinical Decision Support for Postoperative Rehabilitation Planning |
What is being measured
The primary outcome is the main question the study is designed to answer.
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
Measured: From postoperative day 2 (time of AI prediction and potential transfer to rehabilitation area) through 30 days after surgery
Timeline
From the start of the study to its completion; the mark is today. Estimated dates are the sponsor’s plan.
- First posted12 Feb 2026
- Study start1 Jun 2026 (estimated)
- Primary completion1 Jun 2027 (estimated)
- Study completion1 Jul 2027 (estimated)
Resources
- Official record on ClinicalTrials.govThe registry entry this page is built from, with its full change history.
- Other trials for Oncologic SurgeryStudies of the same condition, open and under way.
- More trials run by Erasmus Medical CenterThe sponsor's other registered studies.
- What the trial phases meanHow a treatment moves from first tests in people to approval.
More details
For doctors and researchers: how the study is designed, who runs it, and its registry IDs.
Study design
- Study type
- Interventional
- Phase
- Phase N/A
- Primary purpose
- Diagnosis
- Allocation
- Not applicable
- Intervention model
- Single group
- Masking
- None (open label)
- Enrolment
- 103 participants (estimated)
Sponsor and investigators
- Lead sponsor
- Erasmus Medical Center
- Sponsor type
- University, hospital or other
- Responsible party
- Principal investigator, D.E. Hilling, Erasmus Medical Center
IDs, dates and publications
- ClinicalTrials.gov ID
- NCT07406269
- Sponsor's protocol ID
- DESIRE implementation
- Acronym
- DESIRE
- Status last verified
- Feb 2026
- First submitted
- 6 Feb 2026
- Last updated
- 12 Feb 2026
- Results posted
- No
- Data monitoring committee
- No
- FDA-regulated drug
- No
- FDA-regulated device
- No
- Individual data sharing
- Undecided
Study at a glance
From the registry record, last updated by the sponsor on 12 Feb 2026. Recruitment status is as the sponsor reported it: confirm with the study team.
- Official title
- Evaluation of Clinical Effectiveness and Implementation of an Artificial Intelligence Based Decision Support Tool That Guides Early Rehabilitation After Gastrointestinal and Oncology Surgery
- ClinicalTrials.gov ID
- NCT07406269
- Acronym / sponsor ID
- DESIRE / DESIRE implementation
- Conditions
- Oncologic Surgery, Gastrointestinal Cancers
- Keywords
- Artificial Intelligence, Clinical Decision Support System, Postoperative Care, Early Rehabilitation, Gastrointestinal Surgery, Oncological Surgery, Predictive Modeling
- Study type
- Interventional
- Recruitment status
- Not yet recruiting
- Enrolment
- 103 participants (estimated)
- Lead sponsor
- Erasmus Medical CenterUniversity, hospital or other
- Study start
- 1 Jun 2026 (estimated)
- Primary completion
- 1 Jun 2027 (estimated)
- Study completion
- 1 Jul 2027 (estimated)
- First posted
- 12 Feb 2026 (actual)
- Results
- Not posted in the source record
Clinical summary
The research question as the sponsor registered it. This describes what the study plans to test, not what it found.
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
- Primary purpose
- Diagnosis
- Allocation
- Not applicable
- Intervention model
- Single group
- Masking
- None (open label)
- Number of arms
- 1
| Arm | Type | Receives |
|---|---|---|
| Cohort of 103 patients undergoing GE/oncological surgery and admitted >2 days after surgery | Experimental | Device: DESIRE: AI-Based Clinical Decision Support for Postoperative Rehabilitation Planning |
Who may qualify
- Ages
- 18 years and older
- Sex
- All
- Healthy volunteers
- Not accepted
- Age groups
- Adult, Older adult
Key inclusion criteria (4 listed)
- 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
Key exclusion criteria (2 listed)
- 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
Eligibility is decided by the study team after screening; this overview does not establish that a patient qualifies. Full inclusion and exclusion criteria.
Interventions
| Intervention | Type | Arms |
|---|---|---|
| DESIRE: AI-Based Clinical Decision Support for Postoperative Rehabilitation PlanningThe 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. | Device | Cohort of 103 patients undergoing GE/oncological surgery and admitted >2 days after surgery |
Primary outcome
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
Results and safety
This study is still under way. Results are not available in the source record yet.
Research links
- Official record on ClinicalTrials.govLast updated by the sponsor 12 Feb 2026.
- Individual participant dataSharing planned: Undecided
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Referral and contact
AzTrials does not enrol participants or take referrals. Contact the study team or a site listed below; they decide who can take part.
1 site in 1 country: see every site and its status.
Questions about this trial
What is this clinical trial studying?
A study testing DESIRE: AI-Based Clinical Decision Support for Postoperative Rehabilitation Planning in people with Oncologic Surgery and Gastrointestinal Cancers, run by Erasmus Medical Center at 1 site in Netherlands.
The full registered description is in the About this study section and the official record.
Who may be eligible to take part?
The sponsor lists 4 inclusion and 2 exclusion criteria. Eligibility is decided by the study team after screening, so read the full criteria and contact a listed site.
Is this clinical trial currently recruiting?
The record says: opening soon, as of the sponsor's last update on 12 Feb 2026. Status can change between updates, so confirm with the study contact before making plans.
Where is the study taking place?
The record lists 1 site in Netherlands. Whether a site is taking part right now should be confirmed with that site. See every site.
What are the possible benefits and risks?
They depend on the study and the treatment, and no study can promise a benefit. The study team explains the known risks during informed consent, before anyone joins; the record itself does not list them.
Are results available for this study?
This study is still under way. Results are not available in the source record yet.
How can a doctor refer a patient or contact the research team?
Contact Denise Hilling, MD, PhD (+31 10 704 19 02, d.hilling@erasmusmc.nl), or a site near the patient. AzTrials does not enrol participants or take referrals.
What does the primary outcome measure?
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). It is what the study was designed to measure, not a finding.
Where can I read the original study information?
Does a listing mean the treatment is approved or proven to work?
No. A listing means the study is registered. It does not show that the treatment is safe, works, or is approved by a regulator.
How often is this information updated?
AzTrials copies changed records from ClinicalTrials.gov every night and reloads the whole registry every week. The sponsor last updated this record on 12 Feb 2026.