Big data analytics in healthcare: Optimizing patient outcomes and reducing cost through predictive modeling

Rishi Reddy Kothinti *

Department of Information Systems, University of Texas at Arlington, USA.
 
Review
International Journal of Science and Research Archive, 2022, 07(01), 523-532
Article DOI: 10.30574/ijsra.2022.7.1.0181
Publication history: 
Received on 27 August 2022; revised on 18 October 2022; accepted on 21 October 2022
 
Abstract: 
Big data analytics is changing healthcare by helping doctors improve patient care results while reducing treatment expenses. Predictive modeling helps healthcare providers see what patients need before problems happen and offers better ways to diagnose illnesses and plan unique treatment. This article shows how big data helps healthcare organizations save money while running their operations better.
We can now predict diseases, take early action, and plan resource use better by adding machine learning and AI to our healthcare systems. Healthcare systems resist full implementation of big data solutions because of patient privacy threats, automated decision flaws, and the challenge of connecting separate medical databases.
This article examines big data analytics through existing methods while presenting real examples and discussing upcoming developments. It highlights the need for ethical practices that protect patients while advancing medical advancements. This article explores how technology in healthcare can create better patient care results while reducing healthcare costs. Big data analytics functions as an essential advancement tool to redesign healthcare operations and develop lasting medical innovations for tomorrow
 
Keywords: 
Big Data Analytics; Healthcare; Predictive Modeling; Cost Reduction; Patient Outcomes; Machine Learning
 
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Copyright © 2022 Author(s) retain the copyright of this article. This article is published under the terms of the Creative Commons Attribution Liscense 4.0