 | The 131st Annual Meeting (November 15-19, 2003) of APHA |
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| The 131st Annual Meeting (November 15-19, 2003) of APHA |
David B. Rein, PhD, Atlanta Office, Research Triangle Institute, 1421 Peachtree, #106, Atlanta, GA 30309, 404-685-0285, dhr7@bellsouth.net
Background: Insurers, public health officials, providers, and health management professionals are interested in predicting who uses health care and why. The ability to predict individual variation in health service consumption is important for several practical applications, such as health care financing and targeting health promotion initiatives. Recent research suggests that better predictive estimates of individual level health care utilization are now possible.
Goals: This research seeks to build a better risk adjustment model to predict the use of health services. Specifically, it seeks to predict the health care expenses for the full population of Georgia Medicaid children in 1999 by combining the strengths of two leading cost forecasting models. The model addresses three primary goals; First, to build a better predictive model of health service utilization; second, to address a particular health policy area, that of children with special health care needs (CSHCN), by providing information to help in their definition and categorization; and third, to build upon previous theory in health service utilization, such as the behavioral model of health service utilization and the principle agent model, using knowledge gained from new methodological approaches.
Methods: A new risk adjustment model was developed. The first part of this model used finite mixture methods to identify subpopulations of health care users based on a continuous variable measuring health status. These subpopulations were then used to stratify both portions of a standard two-part risk adjustment model. Results from the new model were compared to traditional models to determine improvements in predictive power. Three separate models were tested, one each for outpatient, inpatient and prescription drug services.
Results: Results from the finite mixture model support the idea of at least four distinct groups of health care users in the Medicaid child data: Healthy children, children with elevated outpatient service use, children with behavioral health conditions, and severely ill children. Models stratified by these groups were superior to standard models. Furthermore, the effects of important explanatory variables often differed between the four health status groups.
Conclusions: Health expenditure models are improved by treating the child Medicaid population as a mixture of several subpopulations. Model improvements can be used to design health care financing strategies for children in Medicaid, to identify different groups of CSHCN, and to expand the theory about who uses health services.
Learning Objectives:
Keywords: HCFA, Cost Issues
Presenting author's disclosure statement:
I do not have any significant financial interest/arrangement or affiliation with any organization/institution whose products or services are being discussed in this session.