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.
| DOI | 10.11648/j.ajtas.20200903.15 |
| Published in | American Journal of Theoretical and Applied Statistics (Volume 9, Issue 3, May 2020) |
| Page(s) | 57-62 |
| Creative Commons |
This is an Open Access article, distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution and reproduction in any medium or format, provided the original work is properly cited. |
| Copyright |
Copyright © The Author(s), 2024. Published by Science Publishing Group |
WTP, Premiums, MLE, Cumulative Ordinal Probit Regression Model, NHIS
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APA Style
Richard Puurbalanta, Mark Adjei, Vida Afosaa. (2020). 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, 9(3), 57-62. https://doi.org/10.11648/j.ajtas.20200903.15
ACS Style
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. Am. J. Theor. Appl. Stat. 2020, 9(3), 57-62. doi: 10.11648/j.ajtas.20200903.15
AMA Style
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. Am J Theor Appl Stat. 2020;9(3):57-62. doi: 10.11648/j.ajtas.20200903.15
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Download@article{10.11648/j.ajtas.20200903.15,
author = {Richard Puurbalanta and Mark Adjei and Vida Afosaa},
title = {Ghana’s National Health Insurance Scheme: An Ordinal Probit Valuation of Willingness to Pay Higher Premiums for Improved Services},
journal = {American Journal of Theoretical and Applied Statistics},
volume = {9},
number = {3},
pages = {57-62},
doi = {10.11648/j.ajtas.20200903.15},
url = {https://doi.org/10.11648/j.ajtas.20200903.15},
eprint = {https://article.sciencepublishinggroup.com/pdf/10.11648.j.ajtas.20200903.15},
abstract = {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.},
year = {2020}
}
TY - JOUR T1 - Ghana’s National Health Insurance Scheme: An Ordinal Probit Valuation of Willingness to Pay Higher Premiums for Improved Services AU - Richard Puurbalanta AU - Mark Adjei AU - Vida Afosaa Y1 - 2020/05/27 PY - 2020 N1 - https://doi.org/10.11648/j.ajtas.20200903.15 DO - 10.11648/j.ajtas.20200903.15 T2 - American Journal of Theoretical and Applied Statistics JF - American Journal of Theoretical and Applied Statistics JO - American Journal of Theoretical and Applied Statistics SP - 57 EP - 62 PB - Science Publishing Group SN - 2326-9006 UR - https://doi.org/10.11648/j.ajtas.20200903.15 AB - 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. VL - 9 IS - 3 ER -
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