A Feasibility Study to Improve Colorectal Cancer Screening Among Racially Diverse Zip Codes in a Persistent Poverty County Using Navigation and Machine Learning Predictive Algorithms

Colorectal Cancer Clinical Trial

— PCSNaP  

Official title:

A Feasibility Study to Improve Colorectal Cancer Screening Among Racially Diverse Zip Codes in a Persistent Poverty County Using Navigation and Machine Learning Predictive Algorithms

Clinical Trial Details — Status: Active, not recruiting

Administrative data

• NCT number: NCT05383976
• Other study ID #: UPCC 09222
• Secondary ID: 850205
• Status: Active, not recruiting
• Start date: February 13, 2023
• Est. completion date: December 2025

Study information

• Verified date: May 2024
• Source: Abramson Cancer Center at Penn Medicine
• Contact: n/a
• Is FDA regulated: No
• Study type: Observational

Clinical Trial Summary

The overarching goals of the "PCSNaP" Research Study is to support the Abramson Cancer Center (ACC) of the University of Pennsylvania in carrying out its mission to increase colorectal cancer (CRC) screening completion among high-risk individuals living in a persistent poverty county by designing, conducting, disseminating and evaluating an electronic health record-based automated identification program to target effective, culturally-sensitive CRC screening navigation to individuals who have not completed an ordered colonoscopy or fecal immunochemical test (FIT).

Recruitment information / eligibility

• Status: Active, not recruiting
• Enrollment: 200
• Est. completion date: December 2025
• Est. primary completion date: December 2025
• Accepts healthy volunteers: Accepts Healthy Volunteers
• Gender: All
• Age group: N/A and older

Eligibility

Inclusion Criteria:

• Patients residing in 18 zip codes in Western and Southwestern Philadelphia who have primary care providers in 4 Penn Medicine Internal Medicine practices and 3 Penn Medicine Family Medicine Practices

• Patients who have had a colonoscopy order placed in the past 6 months and have not scheduled, cancelled, or no-showed to their colonoscopy

Related Conditions & MeSH terms

• Colorectal Cancer
• Colorectal Neoplasms

Intervention

Other:
• Machine Learning Algorithm with Existing Penn Medicine CRC Patient Navigation Program
This intervention will utilize the existing Penn Medicine CRC patient navigation program. There will be a monthly list of patients with unfilled coloscopies provided, that are risk-stratified according to the machine learning algorithm and select high-risk criteria. The navigation team will prioritize timely outreach and navigation to high-risk patients according to a script that communicates risk.

Locations

Country	Name	City	State
United States	University of Pennsylvania	Philadelphia	Pennsylvania

Sponsors (1)

Lead Sponsor	Collaborator
Abramson Cancer Center at Penn Medicine

Country where clinical trial is conducted

United States, 

Outcome

Type	Measure	Description	Time frame	Safety issue
Primary	Enrollment in Navigator Program (Feasibility)	Number of patients that participate in the navigation program	During the three month enrollment period
Primary	Completion of Colorectal Cancer Screening	Number of patients that have completed their colonoscopy or FIT	Within the three month enrollment period and three month follow-up period
Primary	Adenoma Detection Rate	Rate of adenomas after completion of colonoscopy	Within the three month enrollment period and three month follow-up period