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 sufficient-cause model and the counterfactual approach to effect and interaction are tentatively applied to the relationships between risk (prognostic) variables, medical technology, and quality of care. The main conclusions are that quality of care modifies the antagonistic interaction between medical technologies and risk variables, related to different types of responders, as well as the confounding of the effect of risk variables produced by related medical technologies. Thus, confounding of risk factors in the RA method, which limits the latter's predictive validity, is related to the efficacy and complexity of associated medical technologies and to the quality mix of services. Attributional validity depends on the validity of the probabilities estimated for each subgroup of risk (predictive validity) and the percentage of higher-risk patients at each service.