AI model aims to predict cancer Patients' emergency room visits

NCT ID NCT07601802

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

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.

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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

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