The Effect of Information Communication Technology (ICT) on Health Outcomes: Evidence from BRICS-T Countries

Yıl 2022, Cilt: 7 Sayı: 19, 678 - 697, 29.10.2022

Munise Ilıkkan Özgür , Cuma Demirtaş , Zekiye Örtlek

https://doi.org/10.25204/iktisad.1023768

Cited By: 1

Öz

This study analyzes the effects information and communications technology (ICTs) have had on health outcomes on Brazil, Russia, India, China, South Africa (BRICS countries), and Turkey both on a panel and country basis using data from the period 1990 to 2018. The study has created three models. According to the general findings obtained for the panel, the error correction coefficients of the models other than Model II are negative and statistically significant. Based on the variables of income level, number of physicians, education level, and CO2 emissions used in Model I, the number of physicians and education level are seen to negatively affect life expectancy both in the short and long terms, contrary to theoretical expectations, while income level positively and CO2 emissions negatively affect life expectancy. The number of mobile users represents ICTs and negatively affects life expectancy both in the long and short term. Model III includes number of Internet subscribers, and all variables in this model except number of physicians support theoretical expectations. Accordingly, education and income levels have positive effects, and CO2 emissions have a negative effect. The number of Internet subscribers has both long- and short-term negative effects. When evaluating the findings according to country groups, the variable of income level positively and CO2 emissions negatively affect life expectancy in all countries. The variable of number of physicians has a negative value in all models and countries except for China in Model II. Similarly, the variable of education level generally has a negative impact in all models except Model III. All the ICT variables have negative values and negatively affect life expectancy.

Anahtar Kelimeler

Information and Communication Technology, Health, Turkey, BRICS Countries

Bilgi İletişim Teknoloji (BİT) Kullanımının Sağlık Çıktıları Üzerine Etkisi: BRICS-T Ülkeleri Örneği

Öz

Bu çalışmada BRICS ülkelerinde ve Türkiye’de BİT’lerin sağlık çıktısı üzerine etkisi 1990-2018 dönemine ait veriler kullanılarak hem panel geneli hem de ülke bazlı olarak analiz etmiştir. Çalışmada üç model oluşturulmuştur. Panel geneli için elde edilen bulgulara göre Model II dışında diğer modellere ait hata düzelme katsayıları negatif ve istatistiki açıdan anlamlıdır. Model I’de kontrol değişkenleri olarak kullanılan gelir düzeyi, doktor sayısı, eğitim düzeyi ve CO2 düzeyi değişkenlerinden doktor sayısı ve eğitim düzeyi teorik beklentinin tersi yönünde hem kısa dönemde hem de uzun dönemde negatif etkilerken; gelir düzeyi pozitif ve CO2 düzeyi ise negatif etkilemektedir. BİT’leri temsil eden değişkenlerden cep telefon kullanımı hem uzun hem de kısa dönemde negatif etkilemektedir. İnternet kullanımın yer aldığı Model III’te doktor sayısı dışında tüm değişkenler teorik beklentiyi desteklemektedir. Buna göre eğitim ve gelir düzeyi pozitif, CO2 düzeyi negatif etkilemektedir. İnternet kullanımı ise hem uzun hem de kısa dönemde negatif etkiye sahiptir. Gruplara göre bulgular değerlendirildiğinde ise tüm ülkelerde gelir düzeyi değişkeni pozitif, CO2 emisyonu ise negatif etkilemektedir. Doktor sayısı değişkeni Model II’de Çin dışında tüm model ve ülkelerde negatif işarete sahiptir. Benzer şekilde eğitim düzeyi değişkeni de Model III hariç diğer modellerde genel olarak negatif işarettedir. Çalışmanın konusunu oluşturan BİT’e ait değişkenlerin hepsi negatif değere sahip olup yaşam beklentisini olumsuz etkilemektedir.

Anahtar Kelimeler

Bilgi, İletişim ve Teknoloji, Sağlık, Türkiye, BRICS Ülkeleri

Kaynakça

• Afroz, R., Muhibbullah, Md. and Morshed, M. N. (2020). Impact of information and communication technology on economic growth and population health in Malaysia. Journal of Asian Finance, Economics and Business, 7(4), 155-162. https://doi.org/10.13106/jafeb.2020.vol7.no4.155.
• Adeola, O. and Evans, O. (2018). Digital health: ICT and health in Africa. Actual Problems of Economics, 10(208), 2018.
• Arhete, L. E. and Erasmus, R. (2016, 15-19 May). Healthcare service delivery: A literature review, International Association for Management of Technology. IAMOT 2016, Conference Proceedings, 487-505.
• Benvenuto, M., Sambati, F. V. and Viola, C. (2019). The impact of internet usage on health-care expenditures and sustainability. ERAZ 2019, Selected Papers. https://doi.org/10.31410/ERAZ.S.P.2019.95.
• Blackburne, E. F. and Frank, M. W. (2007). Estimation of nonstationary heterogeneous panels. The Stata Journal, 7(2), 197–208. https://doi.org/10.1177/1536867X0700700204.
• Breusch, T. S. and Pagan, A. R. (1980). The lagrange multiplier test and its applications to model specification tests in econometrics. Review of Economic Studies, 47(1), 239-53. https://www.jstor.org/stable/2297111.
• Booth, S. L., Sallis J. F., Ritenbaugh C., Hill, J. O., Birch, L. L., Frank, L. D., Glanz, K., Himmelgreen, D. A., Mudd, M. and Popkin, B. M. (2001). Environmental and societal factors affect food choice and physical activity: rationale, influences, and leverage points. Nutr Rev., 2001(59), 21–36. https://doi.org/10.1111/j.1753-4887.2001.tb06983.x.
• Chandrasekhar, C.P. and Ghosh, J. (2001). Information and communication technologies and health in low income countries: The potential and the constraints. World Health Organization, 79(9), 850-855.
• Damant, J., Knapp, M., Freddolino, P. and Lombard, D. (2017). Effects of digital engagement on the quality of life of older people. Health and Social Care in the Community, 25(6), 1679–1703. https://doi.org/10.1111/hsc.12335.
• Duttaa, U. P., Gupta, H. and Sengupta, P. P. (2019). ICT and health outcome nexus in 30 selected Asian countries: Fresh evidence from panel data analysis. Technology in Society, 59(2019), 101184. https://doi.org/10.1016/j.techsoc.2019.101184.
• Haluzaa, D. and Jungwirth, D. (2015). ICT and the future of health care: aspects of health promotion. Internatıonal Journal of Medıcal Informatics, (84), 48-57. https://doi.org/10.1016/j.ijmedinf.2014.09.005
• Ibeneme, S., Revere, F. L., Hwang, L-Y, Rajan, S., Okeibunor, J. Muneene, D. and Langabeer, J. (2020). Impact of ınformation and communication technology diffusion on HIV and tuberculosis health outcomes among African health systems. Informatics, 7(2), 1-10; https://doi.org/10.3390/informatics7020011
• Iverson, S.A., Howard, K. B. and Penney, B. K. (2008). Impact of ınternet use on health-related behaviors and the patient-physician relationship: a survey-based study and review. Specıal Communıcatıon, Jaoa, 108(12). https://doi.org/10.7556/jaoa.2008.108.12.699.
• Khan, F.H., Pasha, M.A. and Masud, S. (2021). Advancements in microprocessor architecture for ubiquitous-an overview on history, evolution, and upcoming challenges in a ımplementation. Micromachines, 12(665). https://doi.org/10.3390/mi12060665.
• Kırılmaz, H., Kılıç Kırılmaz, S. and Kahraman, M. (2018). Sağlık personelinin bilgi sistemi işlevlerini kullanımları ve örgütsel performansa etkisi. Strategic Public Management Journal, 4(8), 62-80. https://doi.org/10.25069/spmj.474458.
• Kiberu, V. M., Mars, M. and Scott, R. E. (2017). Barriers and opportunities to implementation of sustainable e-health programmes in Uganda: A literature review. African Journal of Primary Health Care and Family Medicine, 9(1), 1-10. https://doi.org/10.4102/phcfm.v9i1.1277.
• Kim, Y., Park, J. Y., Kim, S. B., Jung, I. K., Lim, Y. S. and Kim, J. H. (2010). The effects of internet addiction on the lifestyle and dietary behavior of Korean adolescents. Nutr Res Pract., 4, 51–7. https://doi.org/10.4162/nrp.2010.4.1.51.
• Kouton, J. and Bétila, R. R. and Lawin, M. (2021). The impact of ICT development on health outcomes in Africa: Does Economic Freedom Matter? Journal of the Knowledge Economy, 12:1830–1869.
• Mahmud, A. J., Olander, E., Eriksén, S. and Haglund, B. J. (2013). Health communication in primary health care-A case study of ICT development for health promotion. BMC Medical Informatics and Decision Making, 17 (13). http://www.biomedcentral.com/1472-6947/13/17.
• Mamun, M. A., Sohog, K. and Akhter, A. (2013). A dynamic panel analysis of the financial determinants of CSR in Bangladeshi banking industry. Asian Economic and Financial Review, 3(5), 569-570. http://aessweb.com/journal-detail.php?id=5002.
• Majeed, M. T. and Khan, F. N. (2019). Do information and communication technologies (ICTs) contribute to health outcomes? An empirical analysis. Qual Quant, 53, 183–206. . https://doi.org/10.1007/s11135-018-0741-6.
• May, C. R., Finch, T. L., Cornford, J., Exley, C., Gately, C., Kirk, S., Jenkings, K. N., Osbourne, J., Robinson, A. L., Rogers, A., Wilson, R. and Mair, F. S. (2011). Integrating telecare for chronic disease management in the community: What needs to be done? Health Services Research, 2011, 11: 131.
• Ömürbek, N. and Altın, F. G. (2009). Sağlık bilişim sistemlerinin uygulanmasına ilişkin bir araştırma: İzmir örneği. SDÜ Fen Edebiyat Fakültesi Sosyal Bilimler Dergisi, 19, 211-232.
• Patterson, D. A. (2020). Information technologies. Scientific American, 273(3), (September 1995), 62-67. https://www.jstor.org/stable/10.2307/24981716.
• Pesaran, M. H. (1997). The role of economic theory in modelling the long run. The Economic Journal, 107 (440), 178-191.
• Pesaran, M. H., Shin, Y. and Smith, R. P. (1999). Pooled mean group estimation of dynamic heterogeneous panels. Journal of the American Statistical Association, 94(446), 621-634. https://doi.org/10.1080/01621459.1999.10474156
• Pesaran, M. H. (2004). General diagnostic tests for cross section dependence in panels. Discussion, 1240, 1-42.
• Pesaran, M. H. (2007). A simple unit root test in the presence of cross section dependence. Journal of Applied Econometrics, (22), 265-312. https://doi.org/10.1002/jae.951.
• Pesaran, M., Ullah, A. and Yamagata, T. (2008). A bias-adjusted lm test of error cross-section independence. Econometrics Journal, 11(1), 105-127. https://doi.org/10.1111/j.1368-423X.2007.00227.x
• Peseran, M. H. and Yamagata, T. (2008). Testing slope homogeneity in large panels. Journal of Econometrics, 142(1), 50-93. https://doi.org/10.1016/j.jeconom.2007.05.010.
• Rana, R. H., Alam, K. and Gow, J. (2018). Development of a richer measure of health outcomes incorporating the impacts of income inequality, ethnic diversity, and ICT development on health. Globalization and Health, 14(72). https://doi.org/10.1186/s12992-018-0385-2.
• Reinecke, L., Aufenanger, S., Beutel, M. E., Dreier, M., Quiring, O., Stark, B., Wölfling, K. and Müller, K. W. (2017). Digital stress over the life span: the effects of communication load and internet multitasking on perceived stress and psychological health impairments in a german probability sample. Media Psychology, 20(1), 90-115. https://doi.org/10.1080/15213269.2015.1121832.
• Rosell, M. C., Sánchez-Carbonell, X., Jordana, C. G. and Fargues, M. B. (2007). Adolescents and information and communications technologies: internet, mobile phone and videogames. Papeles del Psicólogo, 2007(28), 196–204. 007. http://www.cop.es/papeles.
• Staras, K., Mačiulienė, M. and Stokaitė, V. (2013). Informacınıų ır komunıkacınıų technologıjų įtaka sveıkatos prıežıūros paslaugų teıkımuı. Onlıne Sveıkatos Polıtıka Ir Valdymas Health Polıcy And Management, 1(5), 148–166. https://doi.org/10.13165/SPV-13-1-5-10.
• Tavares, A. I. (2018). eHealth, ICT and its relationship with self-reported health outcomes in the EU countries. International Journal of Medical Informatics, 112(2018), 104-113. https://doi.org/10.1016/j.ijmedinf.2018.01.014.
• Top, S. and Dilek, S. (2013). Sağlık hizmet sektöründe çalışanların kurumsal bilgi paylaşımı algılamasının ilişki analizi yoluyla değerlendirilmesi. Süleyman Demirel Üniversitesi İktisadi ve İdari Bilimler Fakültesi Dergisi, 18(1), 283-304.
• Viorela Ligia Vaidean, V. L. and Achim, M. V. (2022). When more is less: Do information and communication technologies (ICTs) improve health outcomes? An empirical investigation in a non-linear framework. Socio-Economic Planning Sciences, 80 (2022), 101218.
• Westerlund, J. (2008). Panel cointegration tests of the fisher effect. Aplied Econometrics, 23(2), 193-233. https://doi.org/10.1002/jae.967.
• World Bank (2020). Life expectancy at birth, total (years), Haziran 29, 2021 tarihinde https://data.worldbank.org/indicator/SP.DYN.LE00.IN?locations=TR.
• World Bank (2020). Individuals using the internet (% of population), Haziran 29, 2021 tarihinde https://data.worldbank.org/indicator/SP.DYN.LE00.IN?locations=TR .
• World Bank (2020). Fixed telephone subscriptions (per 100 people), Haziran 29, 2021 tarihinde https://data.worldbank.org/indicator/SP.DYN.LE00.IN?locations=TR .
• World Bank (2020). GDP per capita (constant 2010 US$), Haziran 29, 2021 tarihinde https://data.worldbank.org/indicator/SP.DYN.LE00.IN?locations=TR.
• World Bank (2020). School enrollment, secondary (% gross), Haziran 29, 2021 tarihinde https://data.worldbank.org/indicator/SP.DYN.LE00.IN?locations=TR.
• World Bank (2020). Physicians (per 1,000 people), Haziran 29, 2021 tarihinde https://data.worldbank.org/indicator/SP.DYN.LE00.IN?locations=TR.
• World Bank (2020). CO2 emissions (metric tons per capita), Haziran 29, 2021 tarihinde https://data.worldbank.org/indicator/SP.DYN.LE00.IN?locations=TR.
• World Bank (2020). Mobile cellular subscriptions (per 100 people), Haziran 29, 2021 tarihinde https://data.worldbank.org/indicator/SP.DYN.LE00.IN?locations=TR.
• Yankın, F. B. (2019). Dijital dönüşüm sürecinde çalışma yaşamı. Trakya Üniversitesi İktisadi ve İdari Bilimler Fakültesi E-Dergi, 7(2), 1-38.
• Yücel, D. and Erkut, H. (2003). Bilişim teknolojilerinin çalışma yaşam kalitesi üzerine etkisi. itüdergisi/d mühendislik, 2(2), 49-59.
• Zhang, J., Gong, X. and Zhang, H. (2022). ICT diffusion and health outcome: Effects and transmission channels. Telematics and Informatics, 67 (2022), 101755.
• Zonneveld, M., Patomella, A. H., Asaba, E. and Guidetti, S. (2020). The use of information and communication technology in healthcare to improve participation in everyday life: a scoping review. Disability and Rehabilitation, 42(23), 3416–3423. https://doi.org/10.1080/09638288.2019.1592246.