The Wireless Sensor Network (WSN) in healthcare systems plays a crucial role in continuous patient monitoring, especially in inaccessible areas. We have proposed an enhanced model of the Low Energy Adaptive Clustering Hierarchy (LEACH) protocol, combined with the K-means algorithm, to optimize energy consumption and extend the network lifetime in IoT-based healthcare applications. The proposed method employs a hierarchical approach, clustering sensor nodes and selecting cluster heads (CHs) based on residual energy and proximity to the Base Station (BS). Moreover, sub-cluster heads (Sub-CHs) are introduced to further distribute the energy load and enhance data transmission efficiency. Also, simulation results indicate that the integration of K-means clustering with LEACH significantly improves the selection of efficient CHs, reducing energy loss and increasing the successful data transfer rate to the BS. The proposed method demonstrates a 65.84% improvement in efficiency over traditional protocols and extends the network lifetime by approximately 69.5%, compared to 59.2% with standard LEACH. This approach ensures reliable and continuous monitoring of patients, optimizing the balance between energy consumption and data transmission efficiency in WSN-based healthcare systems.