OBJECTIVES:  CDC guidelines recommend hepatitis C virus (HCV) screening for the 1945-1965 birth cohorts.  Since HCV prevalence is decreasing with birth-year, age-specific screening is less cost-effective in later cohorts.  To inform the optimal time to discontinue screening, collecting additional information may be valuable, though when this information should be collected is unclear.  METHODS: We apply a Markov decision process framework to evaluate how long to continue HCV screening in US men. We identify the optimal information collection policy for two parameters assumed constant across cohorts - reductions in quality-of-life from awareness of HCV-positive status and the fibrosis-stage distribution at screen-detected diagnosis at age 50 - alone and in combination with information collection about HCV prevalence which is decreasing across cohorts.  We estimate lifetime costs and benefits using a previously-developed HCV screening model and HCV prevalence dynamics derived from NHANES.  The assumed willingness-to-pay threshold is $75,000 per QALY.  RESULTS: The presence of a parameter which varies across cohorts influences the per-person value-of-information about both time-varying and static parameters. In these cases, we show analytically that it may be optimal to delay information collection.  Given our prior beliefs, the optimal strategy is to collect sample information about the reduction in quality-of-life from awareness of HCV-positive status immediately and then, depending on the result of that study, collect information on HCV prevalence 3 to 20 years in the future.  This strategy increases the expected incremental net monetary benefit by $2.3 million compared to a strategy of collecting information about both immediately.   CONCLUSIONS:  We demonstrate that when parameters vary across cohorts, the optimal information collection policy, for both time-varying and static parameters, may be to delay information collection until it is more likely to influence the decision. Our dynamic programming framework enables the consideration of delayed information collection in numerous contexts.