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
Study Overview
Status
Status
Conditions
Conditions
Intervention / Treatment
Intervention / Treatment
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.
Study Type
Study Type
Enrollment (Actual)
Enrollment
Phase
Phase
- Not Applicable
Contacts and Locations
Study Locations
-
-
Minnesota
-
Rochester, Minnesota, United States, 55905
- Mayo Clinic in Rochester
-
-
Participation Criteria
Eligibility Criteria
Eligibility Criteria
Ages Eligible for Study
- Adult
- Older Adult
Accepts Healthy Volunteers
Description
Inclusion Criteria:
- Adult patient in Enhanced, Electronic health record (EHR)-facilitated Cancer Symptom Control (E2C2) with a diagnosis of advanced gynecologic malignancy (International Classification of Diseases [ICD] codes C51 through C58)
- Weekly the reviewers will select patients by looking at patients in sorted order starting with the highest score and proceeding down the list and evaluating each patient for exclusion criteria
Exclusion Criteria:
- Patients that have been seen by palliative care will be excluded for 75 days
- Patients under the age of 18 years
- Patients currently enrolled with hospice
Study Plan
How is the study designed?
Design Details
- Primary Purpose: Screening
- Allocation: N/A
- Interventional Model: Single Group Assignment
- Masking: None (Open Label)
Number of Arms
Arms and Interventions
Participant Group / ArmParticipant Group / Arm |
Intervention / TreatmentIntervention / Treatment |
|---|---|
|
Experimental: Screening (AI algorithm)
Patients' medical records are reviewed for consideration of palliative care consult using AI algorithm QW for 6 months.
|
Undergo medical record review
Use AI algorithm
|
What is the study measuring?
Primary Outcome Measures
Primary Outcome Measures
Outcome Measure |
Measure Description |
Time Frame |
|---|---|---|
|
Timely identification for need of palliative care
Time Frame: Up to 6 months
|
Will be measured as time to the electronic record of consult by the palliative care team in the outpatient setting.
|
Up to 6 months
|
Secondary Outcome Measures
Secondary Outcome Measures
Outcome Measure |
Measure Description |
Time Frame |
|---|---|---|
|
Number of palliative care consultations
Time Frame: Up to 6 months
|
Number of palliative care consultations will be assessed as the number of participants who receive palliative care consultations.
|
Up to 6 months
|
|
Number of advanced care planning notes documented in the electronic health record
Time Frame: Up to 6 months
|
Participant electronic health records will be reviewed for the number of advanced care planning notes listed.
|
Up to 6 months
|
|
Number of billing codes International Classification of Diseases, 10th Revision for palliative care
Time Frame: Up to 6 months
|
Participant electronic health records will be reviewed for the number of International Classification of Diseases, 10th Revision (ICD-10) billing codes for palliative care.
|
Up to 6 months
|
|
Positive predictive value of screened patients
Time Frame: Up to 6 months
|
Will be assessed as the number of patients identified by Artificial Intelligence algorithm who actually received palliative care consultation.
|
Up to 6 months
|
|
Performance metrics on reviewer/oncologist handoff
Time Frame: Up to 6 months
|
Will be assessed by agreement statistics and descriptive statistics on time between oncology contact and oncology response.
|
Up to 6 months
|
Collaborators and Investigators
Sponsor
Sponsor
Investigators
Investigators
- Principal Investigator: Rachel D. Havyer, MD, Mayo Clinic in Rochester
Publications and helpful links
Helpful Links
Study record dates
Study Major Dates
Study Start (Actual)
Study Start
Primary Completion (Actual)
Primary Completion
Study Completion (Actual)
Study Completion
Study Registration Dates
First Submitted
First Submitted
First Submitted That Met QC Criteria
First Submitted That Met QC Criteria
First Posted (Actual)
First Posted
Study Record Updates
Last Update Posted (Actual)
Last Update Posted
Last Update Submitted That Met QC Criteria
Last Update Submitted That Met QC Criteria
Last Verified
Last Verified
More Information
Terms related to this study
Additional Relevant MeSH Terms
Other Study ID Numbers
Other Study ID Numbers
- 23-008371 (Other Identifier: Mayo Clinic in Rochester)
- NCI-2023-09943 (Registry Identifier: CTRP (Clinical Trial Reporting Program))
Drug and device information, study documents
Studies a U.S. FDA-regulated drug product
Studies a U.S. FDA-regulated device product
product manufactured in and exported from the U.S.
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