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Modeling Tradeoffs in Reminder Intensity and Navigation for Large-Scale Mailed Stool Testing Programs
Jennifer C Spencer1, Nicole Kluz1, Virginia Mitchell1
1Department of Population Health, Dell Medical School, University of Texas at Austin, Austin, Texas.
Introduction:
Mailed stool testing is effective for increasing colorectal cancer screening, which reduces colorectal cancer incidence and mortality. To scale up mailed programs efficiently, this study examines tradeoffs between total reach, program intensity, and budget impact.
Methods:
A population-based simulation model was adapted to reflect 215,000 underscreened individuals in Federally Qualified Health Centers across a large U.S. state (Texas) over 5 years. Base case parameters and uncertainty ranges for impact and costs across alternative strategies were derived from local program data and literature review conducted in 2025. Comparisons included reminder intensity-(1) no reminders (initial mailing only), (2) low intensity (reminders by letters, texts, or automated calls), and (3) high intensity (staff outreach by phone)-as well as adding patient navigator outreach for participants with positive stool tests. Program designs were compared across 200 probabilistic scenarios under traditional and budget-constrained frameworks.
Results:
Scenarios incorporating navigation were always preferred over those without navigation. Relative to no reminders, low-intensity reminders cost an incremental $108,000 per colorectal cancer case prevented. Adding high-intensity reminders costs a further $193,000 per case prevented. At a fixed budget lower than $13 million over 5 years, a combination of navigation and low-intensity reminders would generally maximize total program impact, although this inflection point varies with the size of the target unscreened population.
Conclusions:
Policymakers facing economic tradeoffs in program design should prioritize patient navigation after positive primary tests, which is cost-efficient, and should consider patient reminders, with the optimal reminder strategy dependent on the target population size and budget.
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