Integrating Well-Being Information and the Multidimensional Adaptive Prediction Process to Estimate Individual-Level Future Health Care Expenditure Levels.
Decades of research exist focusing on the utility of self-reported health risk and status data in health care cost predictive models. However, in many of these studies a limited number of self-reported measures were considered. Compounding this issue, prior research evaluated models specified with a single covariate vector and distribution. In this study, the authors incorporate well-being data into the Multidimensional Adaptive Prediction Process (MAPP) and then use a simulation analysis to highlight the value of these findings for future cost mitigation. Data were collected on employees and dependents of a nationally based employer over 36 months beginning in January 2010. The first 2 years of data (2010, 2011) were utilized in model development and selection; 51239 and 54085 members were included in 2010 and 2011, respectively. The final results were based on prospective prediction of 2012 cost levels using 2011 data. The well-being-augmented MAPP results showed a 5.7% and 13% improvement in accurate cost capture relative to a reference modeling approach and the first study of MAPP, respectively. The simulation analysis results demonstrated that reduced well-being risk across a population can help mitigate the expected upward cost trend. This research advances health care cost predictive modeling by incorporating well-being information within MAPP and then leveraging the results in a simulation analysis of well-being improvement.
1 Healthcare Management Partners, LLC , Franklin, Tennessee.
Aaron R
AR
Wells
2 Center for Health Research, Healthways, Inc. , Franklin, Tennessee.
Xiabo
X
Guo
2 Center for Health Research, Healthways, Inc. , Franklin, Tennessee.
Carter R
CR
Coberley
2 Center for Health Research, Healthways, Inc. , Franklin, Tennessee.
James E
JE
Pope
D005260:Female; D005544:Forecasting; D005102:Health Expenditures / Q000639:trends*; D006801:Humans; D019451:Information Management / Q000458:organization & administration*; D007407:Interviews as Topic; D008297:Male; D008875:Middle Aged; D010549:Personal Satisfaction; D036301:Qualitative Research