eHealth Adoption and its Impact on Life Expectancy : A Comparative Study of Selected BRICS Countries plus TWO

Authors

  • Ebenezer Larnyo  Department of Health Policy and Management, Jiangsu University, School of Management, 301 Xuefu Road, Zhenjiang, Jiangsu Province, China
  • Baozhen Dai  Department of Health Policy and Management, Jiangsu University, School of Management, 301 Xuefu Road, Zhenjiang, Jiangsu Province, China
  • Abigail Larnyo  Faculty of Applied Sciences, University of Ghana, Legon
  • Christabel Seyram Ankah  Department of Computer Science, Kwame Nkrumah University of Science and Technology, Kumasi

DOI:

https://doi.org//10.32628/IJSRST207286

Keywords:

eHealth, Life expectancy, BRICS countries, USA, Ghana

Abstract

The relationship between eHealth adoption and life expectancy is complex. Research outcomes show different and contradictory results on this relationship. How and why eHealth adoption affect life expectancy is still to a large extent not clear. A causal link between the two is yet to be proven. Without such knowledge, effects of increase or decrease in eHealth adoption on life expectancy may be overestimated or underestimated. This study analyzes the relationship between life expectancy at birth and eHealth adoption in healthcare amongst five selected countries; 3 BRICS countries (China, Russia and South Africa), USA and Ghana, taking into account eHealth foundations, electronic health records, use of health eLearning in health sciences, social media and big data.

This cross-sectional study analyzed WHO Global Survey on eHealth data of five selected countries collected between April and August 2015 by calculating and describing the bivariate correlation between the dependent variable and independent variables. A forward linear regression analysis is also applied to determine the predictive capability of the model.

A significant negative correlation was observed between total health expenditure and eLearning overview, ICT development index rank and internet users and between life expectancy at birth and social media with coefficients of rs = -0.95, p = .014, rs = -1.00, p < .001 and rs = -0.96, p < .001 respectively. Apart from social media indicator of eHealth’s eLearning overview that was significantly correlated with life expectancy at birth, no other correlation was observed between life expectancy at birth and any of the indicators of eHealth. The regression analysis of the predictors show a near perfect result of 100% predictive ability of the model. The study observed that countries that incorporated social media into their eHealth action, through the promotion of health messages on social media as a part of health promotion campaigns, managing patient appointments, sought feedback on services, made general health announcements on social media turn to have citizens that have a significant longer life expectancy. In order to realize high life expectancy of citizens, policy measures have to be directed towards investment in social media incorporation into eHealth strategies.

References

  1. Flygt, C., B. Homelius, B. Jacobsson, M. Foldevi and E. Trell (1995). "Essential data set for computer management of distributed primary care services." Medical Informatics 20(4): 331-341.
  2. Fontaine, P., S. E. Ross, T. Zink and L. M. Schilling (2010). "Systematic review of health information exchange in primary care practices." J Am Board Fam Med 23(5): 655-670.
  3. International Health Partnership (2016). UHC 2030: Building an Alliance to Strengthen Health Systems Draft Concept Note–17 June 2016. Geneva:, International Health Partnership.
  4. Kim, T. K. and S. R. Lane (2013). "Government health expenditure and public health outcomes: A comparative study among 17 countries and implications for US health care reform." American International Journal of Contemporary Research 3(9): 8-13.
  5. Pizziferri, L., A. F. Kittler, L. A. Volk, M. M. Honour, S. Gupta, S. Wang, T. Wang, M. Lippincott, Q. Li and D. W. Bates (2005). "Primary care physician time utilization before and after implementation of an electronic health record: a time-motion study." Journal of biomedical informatics 38(3): 176-188.
  6. The General Assembly, U. N. (2015). Resolution A/RES/70/1: Transforming our world: The 2030 Agenda for Sustainable Development. New York (NY): United Nations, United Nations.
  7. The World Bank Group. 2019. 'World Bank country classification', The World Bank Group. http://data.worldbank.org/about/country-and-lending-groups.
  8. van den Heuvel, W. J. and M. Olaroiu (2017). "How important are health care expenditures for life expectancy? A comparative, european analysis." Journal of the American Medical Directors Association 18(3): 276. e279-276. e212.
  9. Van Lerberghe, W. (2008). The world health report 2008: primary health care: now more than ever, World Health Organization.
  10. Wager, K. A., F. W. Lee, A. W. White, D. M. Ward and S. M. Ornstein (2000). "Impact of an electronic medical record system on community-based primary care practices." The Journal of the American Board of Family Practice 13(5): 338-348.
  11. World Health Organization, WHO (1978). World Health Organization, Alma Ata Declaration. Geneva, World Health Organization.
  12. World Health Organization, WHO (2015). Atlas of eHealth country profiles: the use of eHealth in support of universal health coverage: based on the findings of the third global survey on eHealth 2015. Geneva 27, Switzerland.
  13. World Health Organization, WHO (2015). WHO Global Health Observatory Data Repository 2015. Geneva, World Health Organization.
  14. World Health Organization, WHO (2016). Global diffusion of eHealth: making universal health coverage achievable. Report of the third global survey on eHealth. Geneva, Switzerland.
  15. World Health Organization, WHO (2017). BRICS Health and WHO, Country Presence Profile. Geneva, World Health Organization.

International Journal of Scientific Research in Science and Technology

Downloads

Published

2020-04-30

Issue

Volume 7, Issue 2, March-April-2020

Section

Research Articles

License

Copyright (c) IJSRST

Creative Commons License

This work is licensed under a Creative Commons Attribution 4.0 International License.

How to Cite

[1]
Ebenezer Larnyo, Baozhen Dai, Abigail Larnyo, Christabel Seyram Ankah, " eHealth Adoption and its Impact on Life Expectancy : A Comparative Study of Selected BRICS Countries plus TWO, International Journal of Scientific Research in Science and Technology(IJSRST), Online ISSN : 2395-602X, Print ISSN : 2395-6011, Volume 7, Issue 2, pp.470-481, March-April-2020. Available at doi : https://doi.org/10.32628/IJSRST207286