NCT06182332

An Artificial Intelligence Algorithm for Identifying Gynecologic Cancer Patients in Need of Outpatient Palliative Care

Piloting an Artificial Intelligence Algorithm Used to Identify Patients in Need of Outpatient (or Ambulatory) Palliative Care in an Oncology Population

• Status: Completed
• Phase: N/A
• Study type: Interventional
• Enrollment: 221 (actual)
• Sponsor: Mayo Clinic · Academic / Other
• Sex: All
• Age: 18 Years
• Healthy volunteers: Not accepted

Summary

This clinical trial tests an artificial intelligence (AI) algorithm for its ability to identify patients who may benefit from a palliative care consult for gynecologic cancer that has spread from where it first started to nearby tissue, lymph nodes, or distant parts of the body (advanced). A significant delay in referral to palliative care often occurs among patients with cancer. This delay can lead to poorer symptom management, decreased quality of life, and care that does not align with patient goals or values. AI algorithms are computer programs that use step-by-step procedures to solve a problem. In this trial, an AI algorithm is applied to patients' medical records in order to identify patients with a high burden of disease. Information gathered from this study may help researchers learn whether this AI algorithm is useful for identifying patients who could benefit from outpatient palliative care consultation.

Detailed description

PRIMARY OBJECTIVE: I. To pilot an oncology risk prediction model to identify patients who may benefit from outpatient palliative care consultation to improve symptom management and goal-concordant care in this population. OUTLINE: Patients' medical records are reviewed for consideration of palliative care consult using AI algorithm once a week (QW) for 6 months.

Conditions

• Advanced Malignant Female Reproductive System Neoplasm

Interventions

Type	Name	Description
OTHER	Electronic Health Record Review	Undergo medical record review
OTHER	Internet-Based Intervention	Use AI algorithm

Timeline

• Start date: 2023-12-11
• Primary completion: 2024-06-26
• Completion: 2024-07-26
• First posted: 2023-12-26
• Last updated: 2025-04-04

Locations

1 site across 1 country: United States