This paper analyzes the interaction of direct and indirect risk selection in health insurance markets. It is shown that direct risk selection - using measures unrelated to the benefit package like selective advertising or 'losing' applications of high risk individuals - nevertheless has an influence on the distortions of the benefit package caused by indirect risk selection. Direct risk selecti...

We consider the problem of monitoring and comparing medical outcomes, such as surgical performance, over time. Performance is subject to change due to a variety of reasons including patient heterogeneity, learning, deteriorating skills due to aging, etc. For instance, we expect inexperienced surgeons to improve their skills with practice. We propose a graphical method to monitor surgical perfor...

This paper focuses on the issue of the extent to which the present mainstream risk adjustment (RA) methodology for measuring outcomes is a valid and useful tool for quality-improvement activities. The method's predictive and attributional validity are discussed, considering the confounding and effect modification produced by medical care over risk variables' effect. For this purpose, the suffic...

We provide a rigorous proof of granularity adjustment (GA) formulas to evaluate loss distributions and risk measures (value-at-risk) in the case of heterogenous portfolios, multiple systemic factors and random recoveries. As a significant improvement with respect to the literature, we detail all the technical conditions of validity and provide an upper bound of the remainder term at a finite di...

OBJECTIVES Health-care performance comparisons across countries are gaining popularity. In such comparisons, the risk adjustment methodology plays a key role for meaningful comparisons. However, comparisons may be complicated by the fact that not all participating countries are allowed to share their data across borders, meaning that only simple methods are easily used for the risk adjustment. ...

BACKGROUND Comparison of outcomes requires adequate risk adjustment for differences in patient risk and the type of intervention performed. Both unintentional and intentional misclassification (also called gaming) of risk factors might lead to incorrect benchmark results. Therefore, misclassification of risk factors should be detected. We investigated the use of statistical process control tech...

When premiums are community-rated, risk adjustment (RA) serves to mitigate competitive insurers' incentive to select favorable risks. However, unless fully prospective, it also undermines their incentives for efficiency. By capping its volume, one may try to counteract this tendency, exposing insurers to some financial risk. This in term runs counter the quest to refine the RA formula, which wo...

Instrumental variable (IV) and risk adjustment (RA) estimators, including propensity score adjustments, are both used to alleviate confounding problems in nonexperimental studies on treatment effects, but it is not clear how estimates based on these 2 approaches compare. Methodological considerations have shown that IV and RA estimators yield estimates of distinct types of causal treatment effe...