Joint modelling of health insurance, healthcare utilisation, healthcare expenditure and health status: Evidence from Ghana

Abstract

Abstract: The purpose of this paper is to examine the determinants of health insurance, healthcare utilisation, healthcare expenditure, and health status simultaneously. The study used secondary data from the Ghana Socioeconomic Panel Survey. Health insurance, healthcare utilisation, healthcare expenditure, and health status were estimated simultaneously using the conditional mixed process (CMP) framework. The CMP corrects for likely heterogeneity and sample selection bias. The results revealed a significant association between insurance, healthcare utilisation, healthcare expenditure, and health status, implying that regressing these models apart would yield bias and inconsistent estimates making CMP estimates superior to single estimations. The results discovered that gender, age, education, obesity, physical activity, wealth index, household size, dependency ratio, formal-sector work, and savings significantly drive NHIS enrolment. Gender, age, education, obesity, chronic illness, physical activity, wealth index, risky behaviour, and type of illness influenced individuals’ visits to a health facility. The determinants of out-of-pocket payments were gender, chronic illness, wealth index, risky behaviour, distance to a health facility, and fever and diarrhoea sufferers. Finally, drivers of self-assessed health were gender, age, education, chronic illness, physical activity, wealth index, risky behaviour, fever, cold/cough and diarrhoea.

Keywords:

• conditional mixed process
• healthcare utilisation
• healthcare expenditure
• health insurance
• health status

Acknowledgements

The author is grateful to both the Economic Growth Centre at Yale University and the Institute of Statistical, Social, and Economic Research (ISSER) at the University of Ghana for the permission to use the Ghana Socioeconomic Panel Survey dataset.

Disclosure statement

No potential conflict of interest was reported by the author(s).

Table A1. Baseline regression results

Table

Notes

1. See details in Roodman (2011) as the paper extensively treats how to do this.

Additional information

Funding

The author(s) reported there is no funding associated with the work featured in this article.

Notes on contributors

Samuel Sekyi

Samuel Sekyi graduated from the University of South Africa with a PhD in Economics. He is a Senior Lecturer at the Department of Economics, Simon Diedong Dombo University of Business and Integrated Development Studies, Ghana. His main areas of expertise and interest are Microeconometrics, health economics, development economics and agricultural economics. His recent research assessed the contextual dynamics of Ghana’s National Health Insurance Scheme, where he provided rigorous methodological alternatives to healthcare utilisation, financial protection and health status analyses. This current study makes a valuable contribution to the body of knowledge in healthcare decisions by jointly modelling health insurance, healthcare utilisation, healthcare expenditure and health status within the Conditional Mixed Process framework.