Impact of Data Science in Transforming Healthcare Service Delivery

Authors

  • Jae-Hyun Kang Independent Researcher Yuseong-gu, Daejeon, South Korea (KR) – 34168 Author

Keywords:

Data Science, Healthcare Transformation, Machine Learning, Simulation Research, Healthcare Analytics, Big Data, Predictive Modeling, Patient Outcomes, Author Name, Scopus, Springer, Journal Name, Wissira, Journal Short Form, Wissira Press, Wissira Research Lab, Research Gate, SSRN, ISSN, Academia, UGC Care, PubMed, WOS

Abstract

The rapid evolution of data science techniques has introduced transformative changes across diverse sectors, with healthcare being one of the most significantly impacted. This study examines how advanced data analytics, machine learning algorithms, and simulation modeling are being integrated into healthcare service delivery to improve diagnostic accuracy, optimize resource allocation, and enhance patient outcomes. A mixed-methods approach combining a literature review, quantitative statistical analysis, and simulation research was employed. Our findings indicate that data science not only augments clinical decision-making but also fosters more efficient operational practices. The study underscores the need for robust data infrastructure, cross-disciplinary collaboration, and ethical data management practices to maximize the benefits of data science in healthcare. 

References

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Published

2026-04-05

How to Cite

Impact of Data Science in Transforming Healthcare Service Delivery . (2026). International Journal of Engineering Research in Big Data Systems, 3(2), Apr (17-23). https://ijerbds.org/index.php/ijerbds/article/view/49

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