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Application of Big Data Analytics in Precision Medicine: Lesson for Ethiopia

Author

Listed:
  • Misganaw Tadesse Woldemariam

    (Department of Information Science, Jimma University Institute of Technology, Jimma, Ethiopia2Department of Information and Communication Technology, Bonga College of Education, Bonga, Ethiopia)

  • Daniel Gelaw Alemneh

    (University of North Texas, Denton, Texas 76201, USA)

Abstract

In Ethiopia, healthcare service delivery faces various challenges, specifically in relation to prescribing the right medicine to the right patient at the right time. Thus, patients are exposed to challenges ranging from staying on treatment plans longer than necessary, leaving treatment too early and dying of complications. This paper aims to explore the trends, challenges and opportunities of applying big data analytics (BDA) in precision medicine in other locations around the globe and taking lessons for Ethiopia through a systematic review of 14 peer-reviewed articles from three popular databases. The findings indicate that cancer, epilepsy and systemic diseases altogether are areas currently getting big attention. The challenges are attributed to the nature of health data, failure in collaboration of data sharing, ethical and legal issues, interoperability of systems, poor knowledge skills and culture, and poor infrastructure. In addition to the adoption of modern technologies (new and experimental methods, cloud computing, Internet of Things, social networks, etc.), Ethiopia’s government initiative to promote private technological firms could be an opportunity to use BDA in precision medicine in Ethiopia.

Suggested Citation

  • Misganaw Tadesse Woldemariam & Daniel Gelaw Alemneh, 2023. "Application of Big Data Analytics in Precision Medicine: Lesson for Ethiopia," Journal of Information & Knowledge Management (JIKM), World Scientific Publishing Co. Pte. Ltd., vol. 22(06), pages 1-18, December.
  • Handle: RePEc:wsi:jikmxx:v:22:y:2023:i:06:n:s0219649223500533
    DOI: 10.1142/S0219649223500533
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