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AI model aims to predict cancer Patients' emergency room visits

NCT ID NCT07601802

Knowledge-focused Sponsor: University of California, San Francisco Source: ClinicalTrials.gov ↗

What the study statuses mean

This study's is highlighted.

Recruitment status, easiest to join first

Recruiting now
This trial is taking on new participants right now.
Not yet recruiting
Registered, but not yet taking participants.
By invitation only
Not open to general applications. Only people the study team invites can take part.
Paused
Paused for now. It may or may not start again.
Ongoing
Running, but no longer taking on new participants.
Completed This study
The trial has finished. Results may not be published yet.
Stopped early
Stopped early, before it reached the end. That can be for many reasons, including safety.
Cancelled
Cancelled before anyone took part.

Expanded access (not trials)

Expanded access
Not a trial. This treatment can be requested outside a study, case by case, for people who qualify.
Expanded access (paused)
Not a trial. The treatment can normally be requested outside a study, but is unavailable right now.
Expanded access (ended)
Not a trial. The treatment could once be requested outside a study, but no longer can.
Approved
The treatment has been approved, so it is available normally rather than through this programme.

When the status isn't known

Details not published
The full record has not been published yet, so there is little to show here.
Status unknown
This status has not been confirmed recently, so it may be out of date.

First seen Jun 27, 2026 · Last updated Jun 27, 2026

Summary

This study tested a machine learning model that uses electronic health records to predict which cancer patients receiving infusion therapy are at risk of needing emergency care or hospitalization within 30 days. Researchers analyzed data from over 4,700 patients at UCSF. The goal is to help doctors provide extra support to high-risk patients and prevent unplanned hospital visits.

What this could mean

Our plain-language read of the trial. This is informational only, not medical advice or a prediction.

What this could lead to
If successful, this model could help doctors identify cancer patients at high risk of needing emergency care, allowing earlier supportive interventions to prevent hospital visits.
What could go wrong
This is an observational study using existing medical records, not a treatment trial. The model may not work as well in other hospitals or patient groups, and it does not directly improve patient outcomes.

This is an AI summary of the original study and may miss details. Read our disclaimer.

Study facts

What this study's own registry entry says, in plain language.

Participants

4,740 people

The number who actually took part.

Started

Jul 2017

Finished

Mar 2024

Lead sponsor

Other sponsor

The registry's catch-all category, for sponsors it does not file as a company, a government agency, or a research network.

Who can take part

This study's own entry requirements. Only the study team can say for certain whether you qualify.

Who is studied

Adult patients receiving care for cancer

Ages

18 years and older

Sex

Anyone

Healthy volunteers

Not accepted

This study is not open to healthy volunteers. The entry requirements below say who it is open to.

Show the full entry requirements

Copied word for word from the study's registry entry, so the wording is the study team's rather than ours.

Inclusion Criteria: * Patients 18 years or older diagnosed with cancer who receive care at UCSF and/or one of the UCSF affiliate locations. Exclusion Criteria: * Patients under the age of 18. * Patients receiving care as part of a clinical trial.

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Conditions

The condition(s) this trial relates to.

cancer neoplasm

As listed by the trial registrant

The condition terms exactly as the trial's registrant entered them.

Acute care service utilization Cancer

Contacts and locations

Locations

  • University of California, San Francisco

    San Francisco, California, 94143, United States

More trials for these conditions

Other studies related to the condition(s) this trial covers.