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A comparative analysis of claims-based tools for health risk assessment

Published: April 20, 2007
Category: Reports
Authors: Mehmud S, Winkelman R
Country: United States
Language: null
Type: Performance Analysis
Settings: Academic, Hospital

Schaumburg, IL, USA: Society of Actuaries. Japanese translation published by Tokyo Gakugei University.

Society of Actuaries, Schaumburg, IL, USA

This Society of Actuaries research project builds on the work done for the 1996 and 2002 claims-based health risk assessment research projects. The purpose of this study is to evaluate the predictive accuracy of the commercially available claims-based risk assessment tools under different sets of conditions and with different sets of available information. It also provides some information on the tools’ ease of use and other qualitative characteristics. Given the number of possible uses of risk adjusters, and the many different measures available to evaluate risk adjusters, this report does not attempt to identify which model is the best. It is intended primarily to provide useful quantitative information to assist individuals in selecting the appropriate risk-adjustment model for their given circumstances.
The substantial increase in the number of models available in the marketplace is primarily due to an increase in the number of models being offered by each vendor, but new vendors are also present in the marketplace. Overall, the models have become more tailored to the situation for which they are being used and more sophisticated in general.
Throughout this report, the risk-adjustment models are grouped together based on the similarities of their input data sources. This categorization allows for appropriate comparisons since the input data that a risk adjuster uses is a defining characteristic and often the first consideration a purchaser makes in narrowing down the choices for a particular risk-adjustment application. The abbreviations shown in the Inputs column in the tables are defined at the beginning of the results section of this report.

Predictive Risk Modeling,Practice Patterns Comparison,Performance Assessment,United States

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