At a glance
ClinicalIndex Comparison Record- ✓Reside in 18 specified zip codes in Western and Southwestern Philadelphia
- ✓Have primary care provider at one of 7 participating Penn Medicine practices (4 Internal Medicine, 3 Family Medicine)
- ✓Colonoscopy order placed within past 6 months
- ✓Have not yet scheduled, cancelled, or no-showed to colonoscopy appointment
None specified.
Standardized by ClinicalIndex from the ClinicalTrials.gov record · verify against the source.
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
In Brief
An observational study evaluating Machine Learning Algorithm with Existing Penn Medicine CRC Patient Navigation Program for Colorectal Cancer. Completed, enrolled 385 participants across 1 site.
Detailed 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).
Study Details
Timeline
Interventions
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.