Includes bibliographical references (pages 329-334) and index.
Introduction to health risk -- Models for predicting health costs -- Data: the raw material of modeling -- Clinical identification algorithms -- Grouper models -- Development and construction DRGs, DCGs, and ETGs -- Introduction to modeling -- Linear regression models -- The generalized linear model -- Logistic regression models -- Tree-based methods -- Artificial neural networks -- Medicaid risk adjustment -- Risk adjustment in Medicare -- Risk adjustment and health care reform: the example of Massachusetts -- Developing and using predictive models for care management programs -- Provider efficiency assessment and reimbursement using risk adjustment -- Developing a predictive model for depression severity -- A predictive model for disability underwriting profitability -- Predictive modeling and risk adjustment outside the United States