Ghana’s National Health Insurance Scheme: An Ordinal Probit Valuation of Willingness to Pay Higher Premiums for Improved Services
American Journal of Theoretical and Applied Statistics
Volume 9, Issue 3, May 2020, Pages: 57-62
Received: Nov. 18, 2019; Accepted: Apr. 17, 2020; Published: May 27, 2020
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Richard Puurbalanta, Department of Statistics, Faculty of Mathematical Sciences, University for Development Studies, Navrongo Campus, Tamale, Ghana
Mark Adjei, Department of Statistics, Faculty of Mathematical Sciences, University for Development Studies, Navrongo Campus, Tamale, Ghana
Vida Afosaa, Department of Mathematics and Statistics, Faculty of Applied Sciences, Sunyani Technical University, Sunyani, Ghana
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The importance of improved healthcare services under Ghana’s National Health Insurance Scheme (NHIS) is nationwide admitted. However, service improvement for insurance schemes comes with extra cost. To fill the funding gap, insurance schemes typically charge enhanced premiums. This requires clients’ approval and cooperation to implement. For this reason, this study was conducted to assess Ghana’s NHIS subscribers’ willingness to pay (WTP) enhanced premiums for improved services. Some socio-economic and demographic factors were used as covariates. WTP, being the dependent variable, was categorized into high WTP, moderate WTP, low WTP, and no WTP enhanced premiums. The likelihood of a client falling in a particular WTP category was examined using the Cumulative Ordinal Probit (COP) regression model. A likelihood ratio chi-square of 58.82 with p < 0.000 shows that the model was statistically significant, and fit for prediction. Results showed that age-groups 18-30, 30–45, unemployed, tertiary education, and level of income significantly influenced WTP. Predictions showed that for any average national health insurance user, the probability of being in high WTP, moderate WTP, low WTP and no WTP premium are respectively 0.51, 0.27, 0.11 and 0.12. Based on the results of this study, we recommend that Ghana’s NHIS should institute a progressive premium regime in order to cater for the different needs and financial abilities of clients, thus helping to fill the funding gap.
WTP, Premiums, MLE, Cumulative Ordinal Probit Regression Model, NHIS
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Richard Puurbalanta, Mark Adjei, Vida Afosaa, Ghana’s National Health Insurance Scheme: An Ordinal Probit Valuation of Willingness to Pay Higher Premiums for Improved Services, American Journal of Theoretical and Applied Statistics. Vol. 9, No. 3, 2020, pp. 57-62. doi: 10.11648/j.ajtas.20200903.15
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