The Centers for Medicare & Medicaid Services (CMS) recommend covering blood-based tests meeting proposed minimum performance thresholds for colorectal cancer (CRC) screening. Outcomes were compared between currently available stool-based screening tests and a hypothetical blood-based test meeting CMS minimum thresholds. Using the Colorectal Cancer and Adenoma Incidence and Mortality Microsimulation Model (CRC-AIM), outcomes were simulated for average-risk individuals screened between ages 45 and 75 years with triennial multitarget stool DNA (mt-sDNA), annual fecal immunochemical test (FIT), and annual fecal occult blood test (FOBT). Per CMS guidance, blood-based CRC screening was modeled triennially, with 74% CRC sensitivity and 90% specificity. Although not specified by CMS, adenoma sensitivity was set between 10% and 20%. Published adenoma and CRC sensitivity and specificity were used for stool-based tests. Adherence was set at (1) 100%, (2) 30%-70%, in 10% increments, and (3) real-world rates for stool-based tests (mt-sDNA = 65.6%; FIT = 42.6%; FOBT = 34.4%). Assuming perfect adherence, a blood-based test produced ≥19 lower life-years gained (LYG) than stool-based strategies. At the best-case scenario for blood-based tests (100% adherence and 20% adenoma sensitivity), mt-sDNA at real-world adherence achieved more LYG (287.2 vs. 297.1, respectively) with 14% fewer colonoscopies. At 100% blood-based test adherence and real-world mt-sDNA and FIT adherence, the blood-based test would require advanced adenoma sensitivity of 30% to reach the LYG of mt-sDNA (297.1) and ∼15% sensitivity to reach the LYG of FIT (258.9). This model suggests that blood-based tests with CMS minimally acceptable CRC sensitivity and low advanced adenoma sensitivity will frequently yield inferior outcomes to stool-based testing across a wide range of adherence assumptions.

The objective of this study was to assess the impact of local health department (LHD) expenditures on population health measures using counties as the unit of analysis. An observational research design is used to examine whether public health benefits are associated with higher levels of public health funding. Linear probability multivariate regression models with the use of local level cross-sectional and panel data are employed. A 1-year and a 2-year lag structure are also used to quantify the longer term public health effects of changes in LHD expenditures. Analyses were performed at the county level using local data representing 2120 LHDs, covering 48 US states. Expenditure data from the National Association of County and City Health Officials Profile Surveys and public health measures from County Health Rankings Annual Reports are used. Four public health measures are examined-obesity prevalence, sexually transmitted diseases, diabetes prevalence, and human immunodeficiency virus prevalence. Results from cross-sectional, pooled ordinary least squares, and panel data with fixed effects reveal that increased LHD expenditures per capita were not associated with any of the population health outcomes studied. Multivariate linear regression results using a 1- and 2-year lag structure reveal similar results: funding was not significantly predictive of better public health outcomes. The study design did not control for the potential endogeneity of public health funding. More detailed data and robust research approaches are needed to disentangle the effect and effectively answer whether increased public funding translates to improved population health.