Forecasting medical cost inflation rates: A model comparison approach

a r t i c l e i n f o Due to healthcare costs rising faster than overall cost of living, decision makers (i.e., households, businesses, and governments) must cut back on healthcare utilization or spending elsewhere to be fiscally responsible. Accurate forecasts of future medical costs are critical for efficient planning, budgeting and operating decisions at all levels. This research compares the accuracy of the linear autoregressive moving average (ARMA) model and the nonlinear neural network model in producing forecasts of medical cost inflation rates. The analysis focuses on twelve monthly measures of medical costs including the overall medical care price index and eleven (disaggregated) subsectors of medical costs. In addition to standard symmetric measures of forecast accuracy , we utilize two asymmetric error measures designed to capture and penalize preferences for under-and overprediction in model selection. The findings indicate that the neural network model outperforms the uni-variate ARMA in both 1-step and 12-step ahead forecasts. A number of important practical implications are discussed, such as the use of accurate forecasts in contract negotiations, budgeting and planning. Health care spending continues to grow faster than the economy. According to the Centers for Medicare and Medicaid Services, national health expenditures accounts for 16.2% of gross domestic product in 2008. Increases in demand for healthcare products and services from a growing population, consumer price insensitivity, and technology are just some of the factors that continue to put an upward pressure on prices. Rising prices often make operating and budgetary decisions more difficult as the share of these health expenditures relative to the rest of the budget increases. As such, decision makers (i.e., households, businesses, and governments) must cut back on healthcare utilization or spending on other products or services elsewhere. Hence, accurate forecasts of future medical costs are critical for efficient planning, budgeting and operating decisions at all levels (i.e., household, firm, and government). For instance, while many consumers at the household level have some form of insurance, a substantial amount of medical payments are made out-of-pocket. Consequently, many households participate in health savings accounts (HSA). Knowledge about future changes in medical costs would assist households in optimally determining the amount to allocate to their respective HSAs. 1 Budget analysts and financial managers require accurate forecasts of the rate of medical price increases. Medical cost inflation plays a major role in planning future budget obligations or liabilities such as pension …