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The Impact of the Diffusion of Information and Communication Technology on Health: A Cross-Country Study

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Abstract

This study employed aggregate data drawn from the World Bank database for 61 countries for the period 2000 to 2009 and quantitatively evaluated the impact of Information and Communication Technology (ICT) diffusion on health outcomes. The empirical methodology included a dynamic panel data (DPD) model and a fixed effect (FE) model. The results show that the diffusion of the Internet and fixed and mobile telephones was positively associated with life expectancy. The diffusion of fixed and mobile telephones was associated with a reduction in infant and under-five mortality rates. The diffusion of the Internet was associated with a higher prevalence of human immunodeficiency virus (HIV). The diffusion of mobile phones was associated with decreases in the incidence of tuberculosis. An important policy implication for governments worldwide is that investing in ICT infrastructures and educating the public the use of ICT can be an alternative policy to improve health.

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Notes

  1. The 61 countries include Austria, Bahamas, Barbados, Belgium, Bulgaria, Burkina Faso, Chad, Costa Rica, Czech Republic, Denmark, Djibouti, Dominican Republic, El Salvador, Estonia, Fiji, Finland, France, Germany, Ghana, Hungary, Iceland, Indonesia, Ireland, Israel, Japan, Kazakhstan, Korea Republic, Latvia, Lesotho, Lithuania, Malawi, Mauritania, Mauritius, Mexico, Moldova, Netherlands, Niger, Nigeria, Norway, Panama, Paraguay, Peru, Poland, Portugal, Qatar, Romania, Slovak Republic, Slovenia, South Africa, Spain, Sweden, Switzerland, Tajikistan, Tanzania, Turkey, Uganda, Ukraine, United Kingdom, United States, Uruguay, and Uzbekistan.

  2. We adopted the income classification of the World Bank in 2000. The classification was as follows: high-income countries: GNI per capita in US dollars >9265; middle-income countries: GNI per capita in US dollars >755, <9265; low-income countries: GNI per capita in US dollars <755.

  3. Ideally, we would have used the number of ICT users utilizing ICT in health-related activities as the explanatory variables; however, we were unable to find such data on the international scale; hence, we used the number of ICT users as proxy variables.

  4. Specifically, we used principal-component analysis to estimate the components of these three variables. Then, we used the first principal component to generate fitted values and used the fitted values as a new variable, ictfac.

  5. For example, the findings show that the use of mobile phones had a greater effect than other ICT technologies on the prevention of infant mortality, and we infer this result was because of the superior communication functionality of mobile phones, given that the major cause of infant mortality was often time-sensitive and involved the need for immediate communication.

References

  • Amoss, W. P. (2002). The US/Russia Child Health Care Telemedicine Network, InfoDev project No.162-960926. Vishnevskaya-Rostropovich Foundation.

  • Anand, S., & Bärnighausen, T. (2004). Human resources and health outcomes-cross-country econometric study. Lancet, 364, 1603–1609.

    Article  Google Scholar 

  • Anderson, G. F., Frogner, B. K., Johns, R. A., & Reinhardt, U. E. (2006). Health care spending and use of information technology in OECD countries. Health Affairs, 25(3), 819–831.

    Article  Google Scholar 

  • Arellano, M., & Bover, O. (1995). Another look at the instrumental variable estimation of error-components models. Journal of Econometrics, 68(1), 29–51.

    Article  Google Scholar 

  • Berkman, N. D., Sheridan, S. L., Donahue, K. E., Halpern, D. J., & Crotty, K. (2011). Low health literacy and health outcomes: an updated systematic review. Annals of Internal Medicine, 155(2), 97–107.

    Article  Google Scholar 

  • Blundell, R., & Bond, S. (1998). Initial conditions and moment restrictions in dynamic panel data models. Journal of Econometrics, 87(1), 115–143.

    Article  Google Scholar 

  • Booth, S. L., Sallis, J. F., Ritenbaugh, C., Hill, J. O., Birch, L. L., Frank, L. D., & Hays, N. P. (2001). Environmental and societal factors affect food choice and physical activity: rationale, influences, and leverage points. Nutrition Reviews, 59(3), S21–S36.

    Article  Google Scholar 

  • Brodie, M., Flournoy, R. E., Altman, D. E., Blendon, R. J., Benson, J. M., & Rosenbaum, M. D. (2000). Health information, the Internet, and the digital divide. Health Affairs, 19(6), 255–265.

    Article  Google Scholar 

  • Bull, S. S., & McFarlane, M. (2000). Soliciting sex on the internet: what are the risks for sexually transmitted diseases and HIV? Sexually Transmitted Diseases, 27(9), 545–550.

    Article  Google Scholar 

  • Bylund, C. L., Sabee, C. M., Imes, R. S., & Aldridge Sanford, A. (2007). Exploration of the construct of reliance among patients who talk with their providers about internet information. Journal of Health Communication, 12(1), 17–28.

    Article  Google Scholar 

  • Dean. (2001). Constructive conflict in China: cooperative conflict as a bridge between east and west. Journal of World Business, 36(2), 166–183.

    Article  Google Scholar 

  • DeWalt, D. A., & Hink, A. (2009). Health literacy and child health outcomes: a systematic review of the literature. Pediatrics, 124(Supplement 3), S265–S274.

    Article  Google Scholar 

  • Dworkin, S. L., & Ehrhardt, A. A. (2007). Beyond ABC to include GEM (gender relations, economic contexts, and migration movements): critical reflections on progress in the HIV/AIDS epidemic. American Journal of Public Health, 97, 13–16.

    Article  Google Scholar 

  • Dyer, O. (2006). New report on corruption in health. Bulletin of the World Health Organization, 84(2), 84–85.

    Google Scholar 

  • ECOSOC. (2010). Health literacy and the millennium development goals: United Nations economic and social council (ECOSOC) regional meeting background paper (abstracted). Journal of Health Communication: International Perspectives, 15(S2), 211–223.

    Google Scholar 

  • Finkelhor, D. (2011). The internet, youth safety and the problem of “Juvenoia”. A report of the crimes against children research center. Available at http://www.unh.edu/ccrc/pdf/Juvenoia%20paper.pdf.

  • Garofalo, R., Herrick, A., Mustanski, B. S., & Donenberg, G. R. (2007). Tip of the iceberg: young men who have sex with men, the internet, and HIV risk. American Journal of Public Health, 97(6), 1113–1117.

    Article  Google Scholar 

  • Griffiths, F., Cave, J., Boardman, F., Ren, J., Pawlikowska, T., Ball, R., & Cohen, A. (2012). Social networks–the future for health care delivery. Social Science & Medicine, 75(12), 2233–2241.

    Article  Google Scholar 

  • Grossman. (1995). The electronic republic: Resha** democracy in the information age. New York: Penguin.

    Google Scholar 

  • Gupta, S., Verhoeven, M., & Tiongson, E, R. (2002). The effectiveness of government spending on education and health care in develo** and transition economies. European Journal of Political Economy, 18(4), 717–737.

  • Gupta, S., Verhoeven, M., & Tiongson, E, R. (2003). Public spending on health care and the poor. Health Economics, 12(8), 685–696.

  • Gustafsson, E. (2009). Physical exposure, musculoskeletal symptoms, and attitudes related to ICT use, In Department of Public Health and Community Medicine.Gothenburg: University of Gothenburg.

  • Hanseth, O., & Aanestad, M. (2003). Design as bootstrap**: on the evolution of ICT networks in health care. Methods of Information in Medicine, 42(4), 385–391.

    Google Scholar 

  • Hertog, S. (2008). Sex ratios of HIV prevalence: evidence from the DHS. Working paper: United Nations Population Division. Available at: http://paa2008.princeton.edu/abstracts/81156

  • Holtz-Eakin, D., Newey, W., & Rosen, H. (1988). “Estimating vector autoregressions with panel data.” Econometrica, 56(6), 1371−1395.

  • Horvath, K. J., Rosser, B. R. S., & Remafedi, G. (2008). Sexual risk taking among young Internet-using men who have sex with men. American Journal of Public Health, 98(6), 1059–1067.

    Article  Google Scholar 

  • Iannella, R., Robinson, K., & Rinta-Koski, O.-P. (2007). Towards a framework for crisis information management systems, 14th annual conference of the international emergency management society (TIEMS).

  • Kahn, T. (2004). Mobile phones keep track of HIV treatments. Available at: http://www.scidev.net/en/news/mobile-phones-keep-track-of-hiv-treatments.html

  • Keller, S. N., Labelle, H., Karimi, N., & Gupta, S. (2002). STD/HIV prevention for teenagers: a look at the Internet universe. Journal of Health Communication: International Perspectives, 7(4), 341–353.

    Article  Google Scholar 

  • Kim, Y., Park, J. Y., Kim, S. B., Jung, I. K., Lim, Y. S., & Kim, J. H. (2010). The effects of internet addiction on the lifestyle and dietary behavior of Korean adolescents. Nutrition Research and Practice, 4(1), 51–57.

    Article  Google Scholar 

  • Kummervold, P. E., Chronaki, C. E., Lausen, B., Prokosch, H. U., Rasmussen, J., Santana, S., & Wangberg, S. C. (2008). eHealth trends in Europe 2005–2007: a population-based survey. Journal of Medical Internet Research, 10(4).

  • Lee, M. H., & Lio, M. C. (2014). The impact of information and communication technology on public governance and corruption in China. Information Development. doi:10.1177/0266666914529293.

    Google Scholar 

  • Lewis, M. (2006). Governance and corruption in public health care systems. Working Paper No. 78, Washington, D.C.: Center for Global Development

  • Lio, M. C., Liu, M. C., & Qu, Y. P. (2011). Can the internet reduce corruption? A cross-country study based on dynamic panel data models. Government Information Quarterly, 28(1), 47–53.

    Article  Google Scholar 

  • Lucas, H. (2008). Information and communications technology for future health systems in develo** countries. Social Science & Medicine, 66, 2122–2132.

    Article  Google Scholar 

  • McNamara, K. (2007). Improving health, connecting people: the role of icts in the health sector of develo** countries. Working Paper, No. 1, 2007. Washington, DC: infoDev.

  • Micevska, M. B. (2005). Telecommunications, public health, and demand for health-related information and infrastructure. Information Technologies and International Development (ITD), 2(3), 57–72.

    Article  Google Scholar 

  • Musoke, M. (2001). Simple ICTs reduce maternal mortality in rural Uganda: A telemedicine case study. Retrieved from: http://www.medicusmundi.ch/de/bulletin/mms-bulletin/informations-undkommunikationstechnologien/telemedicine/a-telemedicine-case-study

  • Nutbeam, D. (2000). Health literacy as a public health goal: a challenge for contemporary health education and communication strategies into the 21st century. Health Promotion International, 15(3), 259–267.

    Article  Google Scholar 

  • Paasche-Orlow, M. K., & Wolf, M. S. (2007). The causal pathways linking health literacy to health outcomes. American Journal of Health Behavior, 31(Supplement 1), S19–S26.

    Article  Google Scholar 

  • Panir, M. J. H. (2011). Role of ICTs in the health sector in develo** countries: a critical review of literature. Journal of Health Informatics in Develo** Countries, 5(1), 197–208.

    Google Scholar 

  • Ramli, R. (2011). The internet, its social and ethical problem to the young and how curriculum can address the issue. World Academy of Science, Engineering and Technology, 59, 645–648.

    Google Scholar 

  • Ranerup (2000). On-line forums as an arena for political discussions. In Proceeding of digital cities: Technologies, experiences and future perspectives. Berlin: Springer-Verlag.

  • Ratzan, S. C. (2011). Connecting the MDGs and NCDs with digital health. Journal of Health Communication: International Perspectives, 16(7), 681–685.

    Article  Google Scholar 

  • Roodman, D. (2009). How to do xtabond2: an introduction to difference and system GMM in Stata. Stata Journal, 9(1), 86.

    Google Scholar 

  • Rosell, M. C., Sánchez-Carbonell, X., Jordana, C. G., & Fargues, M. B. (2007). Adolescents and information and communications technologies: internet, mobile phone and videogames. Papeles del Psicólogo, 28(3), 196–204.

    Google Scholar 

  • Satellife. (2005). Handhelds for health: Satellife’s experiences in Africa and Asia. Watertown: Satellife.

    Google Scholar 

  • Savedoff, W. D. and Hussmann, K. (2006). Why are health systems prone to corruption? In Global Corruption Report 2006, Berlin: Transparency International, 4–16.

  • Scanfeld, D., Scanfeld, V., & Larson, E. L. (2010). Dissemination of health information through social networks: twitter and antibiotics. American Journal of Infection Control, 38(3), 182–188.

    Article  Google Scholar 

  • Shim, & Eom. (2008). E-Government and anti-corruption: empirical analysis of international data. International Journal of Public Administration, 31(3), 298–316.

    Article  Google Scholar 

  • Sowell, R. L., & Phillips, K. D. (2010). Men seeking sex on an intergenerational gay Internet website: an exploratory study. Public Health Reports, 125(S1), 21–28.

    Google Scholar 

  • Transparency International. (2006). In J. Kotalik & D. Rodriguez (Eds.), Global corruption report 2006. Berlin: Transparency International.

    Google Scholar 

  • UNESCAP/UNDP/ADB. (2007). Achieving the health millennium development goals in Asia and the Pacific: Policies and actions within health systems and beyond. Bangkok: UN Publication.

    Google Scholar 

  • Vogt, M., Hertweck, D., & Hales, K. (2011). Strategic ICT alignment in uncertain environments: An empirical study in emergency management organizations. In System Sciences (HICSS), 2011 44th Hawaii International Conference on (pp. 1–11). IEEE.

  • Walker and Akdeniz (1998). Virtual democracy. Public Law, 489–506.

  • WHO. (2004). e-Health for health-care delivery: Strategy 2004–2007. Geneva: WHO.

    Google Scholar 

  • WHO. (2011). mHealth: New horizons for health through mobile technologies. Global Observatory for eHealth series (Vol. 3). Geneva: World Health Organization.

    Google Scholar 

  • WHO (2012). Children: reducing mortality. Media centre Fact sheet No.178. Available at: http://www.who.int/mediacentre/factsheets/fs178/en/index.html.

  • Wireless Internet Institute (2003). The wireless internet opportunity for develo** countries. Available at: http://www.infodev.org/en/Document.24.PDF.

  • World Bank. (2003). ICT and MDGs: A World Bank Group perspective. Washington: World Bank.

    Google Scholar 

  • **e, B. (2011). Older adults, e‐health literacy, and collaborative learning: an experimental study. Journal of the American Society for Information Science and Technology, 62(5), 933–946.

    Article  Google Scholar 

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Authors and Affiliations

  1. Department of Political Economy, National Sun Yat-sen University, 70, Lienhai Rd., Kaohsiung City, 804, Taiwan

    Ming-Hsuan Lee & Mon-Chi Lio

  2. Department of Business Administration, National Taiwan University, Taipei City, Taiwan

    **-Yu Liu

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  1. Ming-Hsuan Lee
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Correspondence to Ming-Hsuan Lee.

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This research is supported by the National Science Council, Taiwan. Grant number: NSC100-2410-H-110-023-.

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Lee, MH., Liu, PY. & Lio, MC. The Impact of the Diffusion of Information and Communication Technology on Health: A Cross-Country Study. Applied Research Quality Life 11, 471–491 (2016). https://doi.org/10.1007/s11482-014-9376-5

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