Contents |
Authors:
Alina Vysochyna, ORCID: https://orcid.org/0000-0001-9490-1026 Ph.D, Sumy State University, Ukraine Aleksy Kwilinski, ORCID: https://orcid.org/0000-0001-6318-4001 The London Academy of Science and Business, 120 Baker St., London W1U 6TU, UK; Department of Management, Faculty of Applied Sciences, WSB University, 41-300 Dabrowa Gornicza, Poland
Pages: 81-89
Language: English
DOI: https://doi.org/10.21272/hem.2023.1-08
Received: 27.01.2023
Accepted: 10.03.2023
Published: 31.03.2023
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Abstract
Via bibliometric analysis, the research identifies the contextual vectors of the healthcare financial provision effectiveness. Moreover, we broaden the empirical substantiation of panel data regression modelling for 34 European countries. In particular, we define performance of public (budgetary) and private financing to reduce the mortality rate and raise life expectancy in pre-pandemic and pandemic periods. The systematization of existing literature sources and approaches to solving the problem is implemented by means of bibliometric and monographic analysis. Consequently, there are 6 contextual clusters of scientific research on determining the healthcare financial provision effectiveness in the modern science. Within the analysed works, researchers mainly study general prerequisites of the healthcare financial provision effectiveness. The optimal cost formation of medical services for diagnosing and treating diseases is reproduced as well. The issue urgency consists in analysing the efficient patterns of spending various funds to decrease the mortality rate and increase life expectancy in the pre-pandemic and pandemic periods. Subsequently, we detect some general parameters of healthcare resistance to counter shocks similar to the COVID-19 pandemic. In this paper, we show statistical analysis of mortality indexes (total and COVID-19). Among 34 European countries, the highest and lowest efficiency levels were identified within these parameters. The study empirical block constructs 8 regression models on panel data. They differ in dependent (mortality rate or life expectancy) or independent variables (block 1: current and capital healthcare expenditures in GDP; block 2: current healthcare expenditures), and modelling period (pre-pandemic – 2000-2019, pandemic– 2020-2022 or the current period). The modelling results represent financial drivers and change inhibitors of the mortality rate and life expectancy during the pandemic and pre-pandemic periods. Therefore, we established the most effective groups of healthcare expenditures, which is based on the country epidemiological situation. The obtained results can be useful for scientists, representatives of state and local authorities.
Keywords: COVID-19, efficiency, healthcare expenditure, life expectancy, mortality rate.
JEL Classification: C23, H52, I18.
Cite as: Vysochyna, A., & Kwilinski, A. (2023). Efficiency of Healthcare Expenditure in the Pre-Pandemic and Pandemic Periods. Health Economics and Management Review, 4(1), 81-89. https://doi.org/10.21272/hem.2023.1-08
This work is licensed under a Creative Commons Attribution 4.0 International License
References
- Barnes, P.J., Jonsson, B., & Klim, J.B. (1996). The costs of asthma. European Respiratory Journal, 9(4), 636-642. [Google Scholar] [CrossRef]
- Borghouts, J.A.J., Koes, B.W., Vondeling, H., & Bouter, L.M. (1999). Cost-of-illness of neck pain in the Netherlands in 1996. Pain, 80(3), 629-636. [Google Scholar] [CrossRef]
- Cecchini, M., Sassi, F., Lauer, J.A., Lee, Y.Y., Guajardo-Barron, V., & Chisholm, D. (2010). Tackling of unhealthy diets, physical inactivity, and obesity: Health effects and cost-effectiveness. The Lancet, 376(9754), 1775-1784. [Google Scholar] [CrossRef]
- Heidenreich, P. A., Albert, N. M., Allen, L. A., Bluemke, D. A., Butler, J., Fonarow, G. C., … & Trogdon, J. G. (2013). Forecasting the impact of heart failure in the United States: a policy statement from the American Heart Association. Circulation: Heart Failure, 6(3), 606-619. [Google Scholar] [CrossRef].
- Hoberman, A., Wald, E. R., Hickey, R. W., Baskin, M., Charron, M., Majd, M., … & Janosky, J. E. (1999). Oral versus initial intravenous therapy for urinary tract infections in young febrile children. Pediatrics, 104(1), 79-86. [Google Scholar] [CrossRef]
- Dall, T., Nikolov, P., & Hogan, P. F. (2003). Economic costs of diabetes in the US in 2002. Diabetes care, 26, 917-932. [Google Scholar] [CrossRef]
- Kavalieratos, D., Corbelli, J., Zhang, D. I., Dionne-Odom, J. N., Ernecoff, N. C., Hanmer, J., … & Schenker, Y. (2016). Association between palliative care and patient and caregiver outcomes: a systematic review and meta-analysis. Jama, 316(20), 2104-2114. [Google Scholar]
- Kellermann, A.L., & Jones, S.S. (2013). What it will take to achieve the as-yet-unfulfilled promises of health information technology. Health Affairs, 32(1), 63-68. [Google Scholar] [CrossRef]
- Melton III, L. J., Thamer, M., Ray, N. F., Chan, J. K., Chesnut III, C. H., Einhorn, T. A., … & Siris, E. S. (1997). Fractures attributable to osteoporosis: report from the National Osteoporosis Foundation. Journal of Bone and Mineral Research, 12(1), 16-23. [Google Scholar] [CrossRef]
- Scopus (2023). Retrieved from [Link]
- Soumerai, S. B., & Avorn, J. (1990). Principles of educational outreach (‘academic detailing’) to improve clinical decision making. Jama, 263(4), 549-556. [Google Scholar]
- The Stata 14.2/SE Software (2023). Retrieved from [Link]
- VOSviewer (2023). Retrieved from [Link]
- World Bank DataBank (2023). Retrieved from [Link]
- Coronavirus cases. Retrieved from [Link]
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