Background: In the era of digital transformation, real-time health data integration has emerged as a pivotal element in enhancing healthcare management. The exponential growth of data, often referred to as "big data," presents both opportunities and challenges for healthcare providers seeking to improve efficiency and accuracy in patient care. This paper reviews the principles of big data and its implications within the healthcare sector, focusing on the integration of electronic health records (EHRs), Internet of Things (IoT) devices, and advanced data analytics methods.

Methods: To investigate the impact of real-time data integration, a comprehensive literature review was conducted, examining current methodologies used in healthcare data management, including machine learning algorithms and cloud computing technologies. Case studies were analyzed to demonstrate the effectiveness of data integration in reducing medical errors, enhancing patient outcomes, and streamlining workflows.

Results: The findings indicate that healthcare institutions adopting real-time data integration report significant improvements in operational efficiency, with reductions in redundant testing and faster access to critical patient information. Moreover, the integration facilitates proactive healthcare management, allowing practitioners to identify and address health issues before they escalate.

Conclusions: In conclusion, the integration of real-time health data is essential for the evolution of contemporary healthcare management. It not only enhances the quality of care delivered but also supports a more patient-centered approach by leveraging data for personalized treatment strategies. As the healthcare landscape continues to evolve, embracing advanced data integration technologies will be crucial for achieving optimal patient outcomes and operational efficiency.



Keywords: Real-time data integration, healthcare management, big data, electronic health records, Internet of Things