The growing prevalence of non-communicable chronic diseases in Ecuador, evidenced by a survey conducted by the World Health Organization in 2020, which determined that these diseases are the leading cause of disability and death worldwide, has highlighted the urgency of adopting innovative approaches for their management. In this context, Big Data emerges as a transformative tool by integrating large volumes of data from various sources, facilitating more efficient healthcare decision-making. This article explores how Big Data can optimize the prevention, diagnosis, and treatment of non-communicable chronic diseases in Ecuador by identifying patterns and risk factors that might go unnoticed. The integration of data allows for personalized treatments, anticipating complications, and improving resource allocation, thereby reducing costs and improving the quality of life for the population. A mixed methodology combining quantitative and qualitative analysis, epidemiological and clinical data will be examined, applying advanced data mining and machine learning techniques to detect key trends and correlations. Additionally, interviews will be conducted with healthcare professionals to understand the challenges and opportunities in managing these diseases. The results reveal how Big Data can predict outbreaks, personalize treatments, and improve the efficiency of medical resources, providing a comprehensive view that optimizes the management of chronic diseases. In summary, adopting Big Data in Ecuador represents a decisive step towards more efficient, proactive, and personalized healthcare. Despite technological and ethical challenges, its implementation promises to transform the healthcare system and improve long-term care, highlighting the need to continue investing in digital solutions for public health.
| Published in | World Journal of Public Health (Volume 10, Issue 3) |
| DOI | 10.11648/j.wjph.20251003.34 |
| Page(s) | 423-430 |
| Creative Commons |
This is an Open Access article, distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution and reproduction in any medium or format, provided the original work is properly cited. |
| Copyright |
Copyright © The Author(s), 2025. Published by Science Publishing Group |
Big Data Analytics, Digital Health, Health Information Systems Integration, Telemedicine, Remote Patient Monitoring, Electronic Medical Records
| [1] |
Center for Complexity Sciences. (September 11, 2023). Complexity in Health and Ecology: Risks and Data. Retrieved from
https://www.c3.unam.mx/talleres/taller-ComplejidadSaludyEcologia.html |
| [2] |
Polytechnic School of the Litoral. (September 1, 2017). The Big Data Boom in Ecuador. Retrieved from
https://www.espol.edu.ec/sites/default/files/docs_escribe/El%20Boom%20del%20Big%20Data.pdf |
| [3] | Grupo Antico34. (2025). Protección de Datos Sanitarios y Médicos |
| [4] | IBM. (2017, 12 of 30). Data integration. Retrieved from |
| [5] | J. Hurwitz and A. Nugent and F. Halper and M. Kaufman. (2013). Big Data for Dummies. |
| [6] | Jacqueline Vanacek. (2022). Cloud and Big Data are impacting the Human Genome. Touching 7 Billion Lives. Retrieved from Forbes: |
| [7] | Jenkins, E. C., Velarde, M. C. (2018). Polymorphism as a Driver of Human Aging. Frontiers in Genetics. |
| [8] | Khoury MJ, I. J. (2024). Big data meets public health. Science. 2014, 346, 1054-1055. |
| [9] | Luis Joyanes Aguilar. (2024). Big Data: Analysis of Large Volumes of Data in Organization. Alphaomega. |
| [10] | Ministerio de Salud Pública del Ecuador (2022), |
| [11] | Oracle. (2020). Big data issues. Retrieved from |
| [12] | Ruth Lucio, Econ; Nilhda Villacrés, MD; Rodrigo Henríquez. (2021). Ecuadorian Health System. Scielo. |
| [13] | V. Mayer-Schönberger, K. Cukier. (2023). Big Data: A Revolution That Will Transform How We Live, Work, and Think. Houghton Mifflin Harcourt. |
| [14] | Viktor Mayer & Kenneth Cukier. (2023). Big Data. The Big Data Revolution. Turner Publications S. L. |
APA Style
Goyes, F. L. C., Quiñonez, P. B. V. (2025). Transformation in the Management of Chronic Diseases in Ecuador Through the Use of Big Data. World Journal of Public Health, 10(3), 423-430. https://doi.org/10.11648/j.wjph.20251003.34
ACS Style
Goyes, F. L. C.; Quiñonez, P. B. V. Transformation in the Management of Chronic Diseases in Ecuador Through the Use of Big Data. World J. Public Health 2025, 10(3), 423-430. doi: 10.11648/j.wjph.20251003.34
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Download@article{10.11648/j.wjph.20251003.34,
author = {Fabián Lizardo Caicedo Goyes and Polk Brando Vernaza Quiñonez},
title = {Transformation in the Management of Chronic Diseases in Ecuador Through the Use of Big Data
},
journal = {World Journal of Public Health},
volume = {10},
number = {3},
pages = {423-430},
doi = {10.11648/j.wjph.20251003.34},
url = {https://doi.org/10.11648/j.wjph.20251003.34},
eprint = {https://article.sciencepublishinggroup.com/pdf/10.11648.j.wjph.20251003.34},
abstract = {The growing prevalence of non-communicable chronic diseases in Ecuador, evidenced by a survey conducted by the World Health Organization in 2020, which determined that these diseases are the leading cause of disability and death worldwide, has highlighted the urgency of adopting innovative approaches for their management. In this context, Big Data emerges as a transformative tool by integrating large volumes of data from various sources, facilitating more efficient healthcare decision-making. This article explores how Big Data can optimize the prevention, diagnosis, and treatment of non-communicable chronic diseases in Ecuador by identifying patterns and risk factors that might go unnoticed. The integration of data allows for personalized treatments, anticipating complications, and improving resource allocation, thereby reducing costs and improving the quality of life for the population. A mixed methodology combining quantitative and qualitative analysis, epidemiological and clinical data will be examined, applying advanced data mining and machine learning techniques to detect key trends and correlations. Additionally, interviews will be conducted with healthcare professionals to understand the challenges and opportunities in managing these diseases. The results reveal how Big Data can predict outbreaks, personalize treatments, and improve the efficiency of medical resources, providing a comprehensive view that optimizes the management of chronic diseases. In summary, adopting Big Data in Ecuador represents a decisive step towards more efficient, proactive, and personalized healthcare. Despite technological and ethical challenges, its implementation promises to transform the healthcare system and improve long-term care, highlighting the need to continue investing in digital solutions for public health.
},
year = {2025}
}
TY - JOUR T1 - Transformation in the Management of Chronic Diseases in Ecuador Through the Use of Big Data AU - Fabián Lizardo Caicedo Goyes AU - Polk Brando Vernaza Quiñonez Y1 - 2025/09/15 PY - 2025 N1 - https://doi.org/10.11648/j.wjph.20251003.34 DO - 10.11648/j.wjph.20251003.34 T2 - World Journal of Public Health JF - World Journal of Public Health JO - World Journal of Public Health SP - 423 EP - 430 PB - Science Publishing Group SN - 2637-6059 UR - https://doi.org/10.11648/j.wjph.20251003.34 AB - The growing prevalence of non-communicable chronic diseases in Ecuador, evidenced by a survey conducted by the World Health Organization in 2020, which determined that these diseases are the leading cause of disability and death worldwide, has highlighted the urgency of adopting innovative approaches for their management. In this context, Big Data emerges as a transformative tool by integrating large volumes of data from various sources, facilitating more efficient healthcare decision-making. This article explores how Big Data can optimize the prevention, diagnosis, and treatment of non-communicable chronic diseases in Ecuador by identifying patterns and risk factors that might go unnoticed. The integration of data allows for personalized treatments, anticipating complications, and improving resource allocation, thereby reducing costs and improving the quality of life for the population. A mixed methodology combining quantitative and qualitative analysis, epidemiological and clinical data will be examined, applying advanced data mining and machine learning techniques to detect key trends and correlations. Additionally, interviews will be conducted with healthcare professionals to understand the challenges and opportunities in managing these diseases. The results reveal how Big Data can predict outbreaks, personalize treatments, and improve the efficiency of medical resources, providing a comprehensive view that optimizes the management of chronic diseases. In summary, adopting Big Data in Ecuador represents a decisive step towards more efficient, proactive, and personalized healthcare. Despite technological and ethical challenges, its implementation promises to transform the healthcare system and improve long-term care, highlighting the need to continue investing in digital solutions for public health. VL - 10 IS - 3 ER -
Faculty of Engineering, Luis Vargas Torres Technical University, Esmeraldas, Ecuador
Department of Information and Communication Technology, Alberto Enrique Higher Technological Institute, San Lorenzo, Ecuador
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