Adjusted Clinical Groups: predictive accuracy for Medicaid enrollees in three states

Published: September 1, 2002
Category: Bibliography > Papers
Authors: Adams EK, Bronstein JM, Raskind-Hood C
Countries: United States
Language: null
Types: Care Management
Settings: Academic

Health Care Financ Rev 24:43-61.

Rollins School of Public Health, Emory University, Atlanta, GA, USA

Actuarial split-sample method were used to assess predictive accuracy of adjusted clinical groups (ACGs) for Medicaid enrollees in Georgia, Mississippi (lagging in managed care penetration), and California. Accuracy for two non-random groups–high-cost and located in urban poor areas–was assessed. Measures for random groups were derived with and without short-term enrollees to assess the effect of turnover on predictive accuracy. ACGs improved predictive accuracy for high-cost conditions in all States, but did so only for those in Georgia’s poorest urban areas. Higher and more unpredictable expenses of short-term enrollees moderated the predictive power of ACGs. This limitation was significant in Mississippi due in part, to that State’s very high proportion of short-term enrollees.

PMID: 12545598

Cost Burden Evaluation,Predictive Risk Modeling,Financial,United States,Adolescent,Adult,Child,Preschool,Diagnosis-Related Groups/economics,Gender,Infant,Newborn,Managed Care Programs/economics,Medicaid/economics,Middle Aged,Poverty,Pregnancy,Private Sectors,Probability,Reproducibility of Results,State Health Plans/economics,United States,Urban Population

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