Before revision:  In an attempt to accomplish this, risk adjustment formulas include indicators for the presence of health conditions associated with higher costs. The salient issue is that incentives mainly operate at a group level, not an individual level; plans can discriminate at the group level in ways they cannot at the person level. Because health plans providing sparse care for certain illnesses is a key policy concern, group-level fit is arguably one of the most important metrics for formula evaluation. Giving primacy on the basis of individual fit when group fit may be the larger concern can lead to harmful decision making. We therefore discuss the role of p-values and statistical fit for this policy problem while considering the fairness of the risk adjustment algorithm for vulnerable groups.
After revision:  We address some specific limitations of p-values and statistical fit for this policy problem while considering the fairness of the risk adjustment algorithm for vulnerable groups.