In the rapidly evolving landscape of the Internet of Things, efficient communication protocols are essential for managing the vast amount of data generated by interconnected devices. Message Queuing Telemetry Transport is a widely utilized lightweight messaging protocol in IoT applications. Still, the standard MQTT protocol can become inefficient due to the high volume of individual messages, leading to increased network load, latency, and resource utilization. This paper introduces a novel approach to enhance MQTT performance through scalable data aggregation for e-healthcare applications. The proposed architecture significantly reduces network overhead, improves scalability, and optimizes resource usage in IoT applications by aggregating multiple messages into a single JSON object and using MQTT clients as bridges between brokers. The paper details the architecture, implementation, and performance evaluation, demonstrating substantial improvements over existing methods through rigorous mathematical analysis and experimental results.