Forecasting medical cost inflation rates: A model comparison approach

Qing Cao, Bradley T. Ewing, Mark Andrew Thompson

Research output: Contribution to journalArticle

13 Citations (Scopus)

Abstract

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 univariate 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.

Original languageEnglish (US)
Pages (from-to)154-160
Number of pages7
JournalDecision Support Systems
Volume53
Issue number1
DOIs
StatePublished - Apr 1 2012

Fingerprint

Economic Inflation
Costs and Cost Analysis
Neural Networks (Computer)
Costs
Budget control
Negotiating
Contracts
Health Care Costs
Neural networks
Planning
Economics
Delivery of Health Care
Health care
Medical costs
Model comparison
Inflation rate
Model Comparison
Inflation
Research
Budgeting

Keywords

  • ARIMA
  • Forecasting
  • Inflation
  • Medical care
  • Neural networks

ASJC Scopus subject areas

  • Management Information Systems
  • Information Systems
  • Developmental and Educational Psychology
  • Arts and Humanities (miscellaneous)
  • Information Systems and Management

Cite this

Forecasting medical cost inflation rates : A model comparison approach. / Cao, Qing; Ewing, Bradley T.; Thompson, Mark Andrew.

In: Decision Support Systems, Vol. 53, No. 1, 01.04.2012, p. 154-160.

Research output: Contribution to journalArticle

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