Return on Investment of Free Colorectal Cancer Screening Tests in a Primarily Rural Uninsured or Underinsured Population in Northeast Texas

Artificial Intelligence Can Cut Costs While Maintaining Accuracy in Colorectal Cancer Genotyping

Rising cancer care costs impose financial burdens on health systems. Applying artificial intelligence to diagnostic algorithms may reduce testing costs and avoid wasteful therapy-related expenditures. To evaluate the financial and clinical impact of incorporating artificial intelligence-based determination of mismatch repair/microsatellite instability status into the first-line metastatic colorectal carcinoma setting, we developed a deterministic model to compare eight testing strategies: A) next-generation sequencing alone, B) high-sensitivity polymerase chain reaction or immunohistochemistry panel alone, C) high-specificity panel alone, D) high-specificity artificial intelligence alone, E) high-sensitivity artificial intelligence followed by next generation sequencing, F) high-specificity artificial intelligence followed by next-generation sequencing, G) high-sensitivity artificial intelligence and high-sensitivity panel, and H) high-sensitivity artificial intelligence and high-specificity panel. We used a hypothetical, nationally representative, population-based sample of individuals receiving first-line treatment for de novo metastatic colorectal cancer (N = 32,549) in the United States. Model inputs were derived from secondary research (peer-reviewed literature and Medicare data). We estimated the population-level diagnostic costs and clinical implications for each testing strategy. The testing strategy that resulted in the greatest project cost savings (including testing and first-line drug cost) compared to next-generation sequencing alone in newly-diagnosed metastatic colorectal cancer was using high-sensitivity artificial intelligence followed by confirmatory high-specificity polymerase chain reaction or immunohistochemistry panel for patients testing negative by artificial intelligence ($400 million, 12.9%). The high-specificity artificial intelligence-only strategy resulted in the most favorable clinical impact, with 97% diagnostic accuracy in guiding genotype-directed treatment and average time to treatment initiation of less than one day. Artificial intelligence has the potential to reduce both time to treatment initiation and costs in the metastatic colorectal cancer setting without meaningfully sacrificing diagnostic accuracy. We expect the artificial intelligence value proposition to improve in coming years, with increasing diagnostic accuracy and decreasing costs of processing power. To extract maximal value from the technology, health systems should evaluate integrating diagnostic histopathologic artificial intelligence into institutional protocols, perhaps in place of other genotyping methodologies.

Does National Colorectal Cancer Screening Program Represent Good Value for Money? Results from a Return-on-Investment Model in Vietnam

To provide important evidence for the resource allocation process in Vietnam, this research was conducted to explore the return on investment (ROI) of the national colorectal cancer (CRC) screening program. A decision tree model was designed to estimate the cost and cost savings of a national screening program (ie, providing annual fecal occult blood test [FOBT], following with colonoscopy in case of FOBT positive for the medium-risk group over 50 years old) compared to no screening scenario. This was the first attempt in estimating the ROI of a public health program in Vietnam. Although there was a wide variation due to the uncertainty of the input parameters, especially regarding the coverage of the colorectal cancer screening program in the community, the calculated ROI rates in all different cases were positive, demonstrating that the national colorectal cancer screening program brought benefits to the investment. With a modest coverage of 30% of the population over the age of 50, the corresponding ROI value was 325.4% (95%UI: 321.0; 329.9). The results of this study could be used to advocate for the implementation of a national colorectal cancer screening program in terms of the monetary benefits of investing in the program.