Abstract
Using Roy's model of sorting behavior, I study welfare implications of learning about medical care quality through the current health care data production infrastructure that relies on solicitation of research subjects. Due to severe adverse-selection issues, I show that such learning could be biased and welfare decreasing. Direct diversification of treatment receipt may solve these issues but is infeasible. Unifying Manski's work on diversified treatment choice under ambiguity and Heckman's work on estimating heterogeneous treatment effects, I propose a new infrastructure based on temporary diversification of access that resolves the prior issues and can identify nuanced effect heterogeneity.
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