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Predictive Actuarial Modeling of Health Insurance Claims Costs

G. C. Mesike, I. A. Adeleke, Ade Ibiwoye


This study constructs predictive models that can be used in forecasting future health care cost of in-patient diagnoses with high incidence of occurrence for effective health care intervention. Using various forecasting techniques, such as auto-regressive-integrated-moving average and regression, the study aims to find the best fit for data for various health conditions so as to determine the best out-of-sample forecast. The results suggest that while regression modeling was not particularly suitable for the data, Box Jenkins models provide a good fit. The latter models can therefore be used with high degree of accuracy in predicting future costs, thereby facilitating more effective intervention in health care management.


Health Insurance, claims costs, predictive modeling, health care intervention.

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