Improving Colorectal Cancer Screening in Racially Diverse Zip Codes Using Navigation and Machine Learning (PCSNaP)

NCT05383976 | Completed Results

• 2 other identifiers: UPCC 09222850205
• Study Type: observational
• Target: 385
• Locations: 1 country
• Sites: 1

Brief Summary

The overarching goal 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).

Conditions

Colorectal Cancer

Outcome Measures

Primary Outcomes (3)

• Enrollment in Navigator Program (Feasibility)

  Number of patients that participate in the navigation program

  During the three month enrollment period

• Completion of Colorectal Cancer Screening

  Number of patients that have completed their colonoscopy or Fecal Immunochemical Test (FIT)

  Within the three month enrollment period and three month follow-up period

• Number of Participants With Adenoma Detection

  Rate of adenomas after completion of colonoscopy

  Within the three month enrollment period and three month follow-up period

Study Arms (1)

Patients Residing in 18 zip codes in Western and Southwestern Philadelphia

The cohort will consist of 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.

Other: Machine Learning Algorithm with Existing Penn Medicine CRC Patient Navigation Program

Interventions

Machine Learning Algorithm with Existing Penn Medicine CRC Patient Navigation Program OTHER

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.

Patients Residing in 18 zip codes in Western and Southwestern Philadelphia

Eligibility Criteria

• Sex: all
• Healthy Volunteers: Yes
• Age Groups: Child (0-17), Adult (18-64), Older Adult (65+)
• Sampling Method: Non-Probability Sample

Study Population

The cohort will consist of 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 will have had a colonoscopy order placed in the past 6 months and have not scheduled, cancelled, or no-showed to their colonoscopy.

You may qualify if:

• 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

You may not qualify if:

• Not applicable

Sponsors & Collaborators

• Abramson Cancer Center at Penn Medicine: lead

Study Sites (1)

University of Pennsylvania

Philadelphia, Pennsylvania, 19104, United States

Location

MeSH Terms

Conditions

Colorectal Neoplasms

Interventions

Machine Learning Algorithms

Condition Hierarchy (Ancestors)

Intestinal Neoplasms; Gastrointestinal Neoplasms; Digestive System Neoplasms; Neoplasms by Site; Neoplasms; Digestive System Diseases; Gastrointestinal Diseases; Colonic Diseases; Intestinal Diseases; Rectal Diseases

Intervention Hierarchy (Ancestors)

Algorithms; Mathematical Concepts

Results Point of Contact

• Title: Yvette Frimpong
• Organization: Abramson Cancer Center at Penn Medicine

Yvette.Frimpong@pennmedicine.upenn.edu

(215) 573-5107

Study Officials

• Carmen Guerra, MD

  University of Pennsylvania

  PRINCIPAL INVESTIGATOR

Publication Agreements

• PI is Sponsor Employee: Yes

Study Design

• Study Type: observational
• Observational Model: COHORT
• Time Perspective: PROSPECTIVE
• Sponsor Type: OTHER
• Responsible Party: PRINCIPAL INVESTIGATOR
• PI Title: Principle Investigator

Study Record Dates

• First Submitted: May 17, 2022
• First Posted: May 20, 2022
• Study Start: March 29, 2022
• Primary Completion: November 1, 2024
• Study Completion: November 1, 2024
• Last Updated: February 11, 2026
• Results First Posted: February 11, 2026

Record last verified: 2024-11

Locations

US (1)