This study introduces the design and development of an Internet of Wearable Things-based Hybrid Healthcare Monitoring System (IoWT-HHMS) for smart medical applications. The system incorporates smart wearable sensing units for real-time, remote monitoring of vital health parameters such as Blood Pressure (BP), Heart Rate (HR), and Body Temperature (BT). A key innovation is the development of a hybrid wireless network communication mechanism within the IoWT-HHMS, utilising the FiPy microcontroller. This mechanism supports both short- and long-range connectivity and integrates an algorithm for efficient data acquisition and updating to the IoT platform. The IoWT-HHMS has undergone extensive testing and validation across various scenarios, including sensor functionality, performance of Wi-Fi and LoRaWAN networks, hybrid network connectivity, and accuracy assessment using the Datacake dashboard. The tests evaluated crucial aspects such as communication reliability, power consumption, and latency. The results demonstrate the system's high stability and accuracy in reading health parameters. Comparisons with reference devices reveal impressive accuracy levels for Systolic BP (SBP), Diastolic BP (DBP), HR, and BT, recording 96.37 %, 95.17 %, 97 %, and 98.57 % accuracy, respectively. Both Wi-Fi and LoRaWAN networks proved reliable in indoor and outdoor settings, maintaining data transmission over distances up to 1.5 km without data loss. In conclusion, the developed IoWT-HHMS shows great promise for efficient and effective real-time remote monitoring of patients' health conditions using an innovative hybrid wireless network communication mechanism.