Predictive analytics in emergency healthcare systems: A conceptual framework for reducing response times and improving patient care
1 Independent Researcher, Abuja, Nigeria.
2 Department of Business Administration, Texas A&M University Commerce, TX, USA.
3 Etihuku Pty Ltd, Midrand, Gauteng, South Africa.
Review
World Journal of Advanced Pharmaceutical and Medical Research, 2024, 07(02), 119–127.
Article DOI: 10.53346/wjapmr.2024.7.2.0050
Publication history:
Received on 08 October 2024; revised on 14 November 2024; accepted on 17 November 2024
Abstract:
This review paper explores the role of predictive analytics in enhancing emergency healthcare systems, emphasizing the potential benefits of reducing response times and improving patient care. Emergency healthcare systems often grapple with inefficiencies that can adversely affect patient outcomes, especially during critical situations. This paper presents a conceptual framework that leverages predictive analytics to address these challenges by integrating diverse data sources, utilizing real-time analysis, and providing decision-support tools. The findings suggest that predictive analytics can significantly enhance operational efficiency by optimizing resource allocation, streamlining patient prioritization, and enabling timely interventions. Additionally, practical recommendations are proposed for healthcare institutions to successfully implement predictive analytics, including investing in data infrastructure, fostering a culture of analytics, and collaborating with technology partners. This framework paves the way for improved emergency response and contributes to a data-driven healthcare environment that enhances overall patient outcomes.
Keywords:
Predictive Analytics; Emergency Healthcare; Response Times; Patient Care; Data Integration; Decision-Support Tools
Full text article in PDF:
Copyright information:
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