Most cost-effectiveness analyses of colorectal cancer (CRC) screening assume Medicare payment rates and a lifetime horizon. Our aims were to examine the implications of differential payment levels and time horizons for commercial insurers vs. Medicare on the cost-effectiveness of CRC screening.
We used our validated Markov cohort simulation of CRC screening in the average risk US population to examine CRC screening at ages 50-64 under commercial insurance, and at ages 65-80 under Medicare, using a health-care sector perspective. Model outcomes included discounted quality-adjusted life-years (QALYs) and costs per person, and incremental cost/QALY gained.
Lifetime costs/person were 20-44% higher when assuming commercial payment rates rather than Medicare rates for people under 65. Most of the substantial clinical benefit of screening at ages 50-64 was realized at ages ≥65. For commercial payers with a time horizon of ages 50-64, fecal occult blood testing (FOBT) and fecal immunochemical testing (FIT) were cost-effective (<$61,000/QALY gained), but colonoscopy was costly (>$185,000/QALY gained). Medicare experienced substantial clinical benefits and cost-savings from screening done at ages <65, even if screening was not continued. Among those previously screened, continuing FOBT and FIT under Medicare was cost-saving and continuing colonoscopy was highly cost-effective (<$30,000/QALY gained), and initiating any screening in those previously unscreened was highly effective and cost-saving.
Modeling suggests that CRC screening is highly cost-effective over a lifetime even when considering higher payment rates by commercial payers vs. Medicare. Screening may appear relatively costly for commercial payers if only a time horizon of ages 50-64 is considered, but it is predicted to yield substantial clinical and economic benefits that accrue primarily at ages ≥65 under Medicare.
1Division of Gastroenterology and Hepatology, Stanford University School of Medicine, Stanford, CA, USA. 2Department of Medicine, Stanford University School of Medicine, Stanford, CA, USA. 3Predictive Health, Paradise Valley, AZ, USA. 4Department of Family, Community and Preventive Medicine, University of Arizona College of Medicine - Phoenix, Phoenix, AZ, USA. 5Department of Health Research and Policy, Stanford University School of Medicine, Stanford, CA, USA. 6National Bureau of Economic Research, Cambridge, MA, USA.
Correspondence: U.L. (email: email@example.com)
Received 7 December 2017; accepted 9 April 2018; Published online 15 June 2018