Candidate for the Lee B. Lusted Student Prize Competition
Purpose: Several recent analyses (e.g., Ann. Intern. Med. 156(4):263, 2012) indicate that universal one-time screening for hepatitis C (HCV) is likely cost-effective for individuals currently aged 40-60. Since the prevalence of HCV is decreasing with birth-year, screening future cohorts will be less cost effective. Maximizing social value of a HCV screening program requires lifecycle evaluation of its costs and benefits in the presence of the options to continue with or without costly information collection or to terminate the program.
Methods: We apply a Markov decision process framework to evaluate a policy of universal HCV screening. The incremental net monetary benefit of screening a single cohort is linear in the uncertain time-varying parameter, cohort prevalence. We estimated the lifetime cost and benefit of each screening outcome using an HCV natural history model (Liu et al., in prep.), HCV prevalence dynamics using regression to birth-cohort specific prevalence in NHANES, and the cost of information from the US National HIV Behavioral Surveillance System. The willingness-to-pay threshold is assumed $75,000/QALY. Value iteration yields the optimal HCV screening and information collection policy for US men and women.
Results: Without any information collection, the optimal time to stop universal one-time hepatitis C screening is in 36 years (95%CI: 30-41 years) for men and in 15 years (95%CI: 7-21 years) for women. For men, the value of collecting sample information about the HCV prevalence immediately likely does not exceed the cost of collecting information. For women, immediate sampling (n*WOMEN=2400) increases the expected value of an HCV screening policy from $259.2 million to $261.4 million. However, provided a standing option to collect sample information about prevalence the optimal policy is to screen men and women without information collection for 31 years and 11 years, respectively, and then to collect sample information (n**MEN=2000, n**WOMEN=2250) to inform the next action. The expected value of this strategy is $1.149 billion (cf. $1.145 billion with no information collection) and $265.1 million.
Conclusions: Maximizing social value from a health program, such as HCV screening, requires a complete policy lifecycle analysis. By incorporating the expected prevalence dynamics and solving the problem as a Markov decision process we were able to increase the expected value of an HCV screening program by identifying the optimal time to collect HCV prevalence information.