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Acute Risk Monitoring for Oncology Therapy Regimen

NCT07601802 · Status: COMPLETED · Type: OBSERVATIONAL · Enrollment: 4740

Last updated 2026-05-22

No results posted yet for this study

Summary

Patients undergoing outpatient infusion systemic therapy for cancer are at risk for potentially preventable, unplanned acute care in the form of emergency department (ED) visits and hospitalizations. These events impact patient outcomes, treatment decisions, and healthcare costs. To address this need, the Centers for Medicare \& Medicaid Services developed the chemotherapy measure (OP-35). Recent randomized controlled studies indicate that electronic health record (EHR)-based machine learning (ML) approaches accurately direct supportive care to reduce acute care during radiotherapy. This study aims to develop and prospectively validate ML approaches to predict the risk of OP-35 qualifying, potentially preventable, acute care events within 30 days of infusion systemic therapy.

Conditions

  • Cancer
  • Acute Care Service Utilization

Interventions

OTHER

Medical record review

Retrospective chart reviews for data collection will be conducted.

Sponsors & Collaborators

Principal Investigators

  • Julian Hong, MD, MS · University of California, San Francisco

Eligibility

Min Age
18 Years
Sex
ALL
Healthy Volunteers
No

Timeline & Regulatory

Start
2017-07-01
Primary Completion
2024-03-31
Completion
2024-03-31

Countries

  • United States

Study Locations

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Entities

Diseases
Companies

Read the full study record

This page highlights key information. For complete eligibility criteria, study locations, investigator contacts, and the full protocol, visit the original record on ClinicalTrials.gov.

View NCT07601802 on ClinicalTrials.gov