Forecasting the National Health Insurance Fund Membership Enrolment in Tanzania Using the SARIMA Model
DOI:
https://doi.org/10.51867/scimundi.4.2.4Keywords:
ARIMA, Box- Jenkins, National Health Insurance, SARIMA, SeasonalAbstract
This paper aimed at forecasting membership enrolment in the National Health Insurance Fund (NHIF) in Tanzania using quarterly time series data. This study used 88 time series data to fit the seasonal Autoregressive Integrated Moving Average model (SARIMA). ARIMA (3,1,1) (0,1,0)[4] model was built and used for forecasting. The results show that there will be an increasing membership enrolment overtime over the years and no signs of decreasing. Thus, the government, apart from continuing subsidizing the cost of accessing health insurance services, should also improve the National Health Insurance (NHI) coverage to accommodate the increased enrolment and discourage dropouts. In turn, this will help to achieve the Universal Health Coverage (UHC) ultimate aim of ensuring equitable access to essential and manageable healthcare services, regardless of individuals’ financial situations, their location, and personality.
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