Data analytics in healthcare: A review of patient-centric approaches and healthcare delivery
1 Harrisburg University of Science and Technology, Harrisburg, Pennsylvania, United States of America.
2 Independent Researcher, UK.
3 Independent Researcher, Colorado.
4 Dangote Sugar Refinery Plc, Lagos Nigeria.
5 Spacepointe Limited, River State, Nigeria.
6 Department of Information Management, Ahmadu Bello University, Zaria, Nigeria.
Review Article
World Journal of Advanced Research and Reviews, 2024, 21(02), 1750–1760
Article DOI: 10.30574/wjarr.2024.21.2.0246
Publication history:
Received on 09 December 2023; revised on 17 January 2024; accepted on 19 January 2024
Abstract:
The integration of data analytics in healthcare has revolutionized the industry, ushering in a new era of personalized and patient-centric approaches to healthcare delivery. This review explores the multifaceted role of data analytics in reshaping the landscape of healthcare, with a specific focus on patient-centric methodologies and their impact on healthcare delivery. The advent of electronic health records (EHRs) and wearable devices has generated an unprecedented volume of healthcare data. Leveraging advanced analytics, healthcare providers can extract valuable insights from this data to enhance patient care. Patient-centric approaches involve the utilization of individualized health data to tailor treatment plans, predict disease outcomes, and optimize preventive measures. This review delves into the methodologies employed in patient-centric data analytics, examining the utilization of machine learning algorithms, predictive modeling, and artificial intelligence to develop personalized healthcare interventions. Furthermore, the review explores the transformative impact of data analytics on healthcare delivery. The optimization of operational processes, resource allocation, and the identification of cost-effective interventions are vital components of healthcare management. By harnessing the power of data analytics, healthcare systems can streamline their operations, reduce inefficiencies, and allocate resources more effectively. Additionally, predictive analytics aids in forecasting disease outbreaks, enabling proactive measures for containment and resource allocation. The review also highlights the ethical considerations and challenges associated with the implementation of data analytics in healthcare. Patient privacy, data security, and the responsible use of sensitive health information are critical aspects that demand careful attention in the era of digital healthcare. This review underscores the pivotal role of data analytics in fostering patient-centric healthcare approaches and optimizing healthcare delivery. As the healthcare industry continues to evolve, the integration of advanced analytics promises to revolutionize the way healthcare is administered, ensuring a more personalized, efficient, and effective approach to patient well-being.
Keywords:
Data Analytics; Healthcare; Patient-centric; Health; Review
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Copyright © 2024 Author(s) retain the copyright of this article. This article is published under the terms of the Creative Commons Attribution Liscense 4.0