OBJECTIVES: The primary purposes of this paper are 1) to conceptualize new policy decision-relevant metrics to forecast the returns from v policy choices that are designed to provide access and to implement the use of medical technologies in practice and 2) to illustrate this framework and the methods using a styled example of the uptake of combination lipid therapy with a statin plus a fibrate versus statin monotherapy among patients with type 2 diabetes mellitus (T2DM) and mixed dyslipidemia METHODS: First, we have incorporated selective adoption across different subgroups driven by heterogeneous treatment effect to modify the traditional cost-effectiveness ratio. Then, we made these adoption rates to be dependent on policy decisions to capture the realized value of medical technology through the lens of policy alternatives. Also, we tie in other metrics on value of information literature with this framework RESULTS: In the empirical example, we found that the rates of adoption of combination therapy among men, who anticipated higher benefits of combination therapy based on clinical evidence, were twice as high as among women. (3.1% vs. 1.6%) After incorporating this selective behavior among men and women, the realized ICER is $40,670/quality-adjusted life year (QALY), which is lower than the traditional ICER of $45,985/QALY. Among policy alternatives, a policy option to improve implementation of current practice guideline would provide the largest economic returns. In a scenario that 50% of male and 10% of female receive the combination therapy of fibrate and statin, instead of statin monotherapy, the economic returns would be $1,640 per patient.  CONCLUSIONS: The enriched metrics can directly inform policy makers about the level of access and investment in implementation that would produce the largest returns in the context of a new treatment. We believe that the framework and the methods presented can be more decision-friendly for policy makers.