A structural equation modeling approach to examining the predictive power of determinants of individuals' health expenditures.
Understanding the determinants of health expenditures is essential for a fair and effective utilization profiling, particularly in the setting of capitation rates in risk-adjustment models. The objective of the study was to examine the relative importance of determinants in predicting future health expenditures, using structural equation modeling. Based on Andersen's behavioral system model, individual determinants along with prior utilization and measures of health status from 1994 are evaluated in a longitudinal design for theirpredictive powerfor health expenditures in 1995. A total of 4,255 policy-holders enrolled in three health plans at Trigon BlueCross/BlueShield of Virginia who responded to a mail survey were included for analysis. Person-level annual charges for health services utilization were used as the dependent variable. Five health scales were excerpted from Health Survey SF-36 to represent an individual's health status. Excluding prior utilization in 1994, health status (gamma = -0.19, p < 0.001) and having diabetes (gamma = 0.08, p < 0.001) are two statistically significant predictors of health expenditures in 1995. Including prior utilization, both health status (gamma = -0.15, p < 0.001) and prior utilization (gamma = 0.15, p < 0.001) are the most important predictors, followed by having diabetes (gamma = 0.08, p < 0.001). Health status is a powerful predictor offuture health expenditures, even when prior utilization is controlled.
Chern
Jin-Yuan
JY
Department of Health Care Administration, Chang-Jung University, Tainan, Taiwan.
Wan
Thomas T H
TT
Begun
James W
JW
D000328:Adult; D054598:Blue Cross Blue Shield Insurance Plans; D005260:Female; D005544:Forecasting; D005102:Health Expenditures / Q000706:statistics & numerical data*; D006296:Health Services / Q000706:statistics & numerical data; D006305:Health Status Indicators; D006801:Humans; D008137:Longitudinal Studies; D008297:Male; D008875:Middle Aged; D015233:Models, Statistical; D020379:Risk Adjustment; D014768:Virginia / Q000453:epidemiology