Predictive analytics in emergency healthcare systems: A conceptual framework for reducing response times and improving patient care
Vyvyenne Michelle Chigboh, Stephane Jean Christophe Zouo, Jeremiah Olamijuwon · World Journal of Advanced Pharmaceutical and Medical Research · 2024
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.