OBJECTIVES: It has been recommended that due to a lack of evidence, screening for hereditary hemochromatosis should be rejected and instead, further research is warranted. This study builds on a published quantitative synthesis of evidence and assesses the expected value of perfect information (EPVI) as an upper bound of value for further research. Implications of modelling results and EVPI for both Bayesian and Frequentist decision makers with different cost-effectiveness thresholds are discussed. METHODS: Expected value of information both for the decision, for single and for groups of parameters are calculated. Population EVPI was based on an infinite time horizon for the target cohort of 30 years old Germans. RESULTS: A Frequentist decision maker can be assumed to reject screening based on a lack of high quality evidence of cost-effectiveness at thresholds between 50,000 and 100,000 EUR/LYG. In contrary, for a Bayesian with a cost-effectiveness threshold of 50,000 or beyond 100,000 EUR/LYG evidence may be sufficient: The former will probably reject, the latter pursue population screening. The overall costs of uncertainty for the decision are comparatively small: the total expected value of perfect information at a cost-effectiveness threshold of 50,000 EUR/LYG was calcu-lated to be approximately 1 million EUR. Uncertainty about compliance had the highest expected value of partial perfect information of approx. 200,000 EUR. CONCLUSION: Further research on genetics in healthcare should include the issue of patient compliance. Frequentist decision making incurs costs in terms of expected health forgone. Yet the Frequentist decision is more stable: Given the deterioration of cost-effectiveness ratios in past economic studies, a Bayesian decision maker with a threshold of EUR 50,000 / LYG may have introduced screening years ago while a Frequentist decision maker would always have rejected it. Coverage with evidence development may bridge the gap between both.