The increasing importance of intra-vehicular health monitoring systems (IVHMS) necessitates robust communication protocols within vehicles, especially with the integration of the Internet of Things (IoT). This integration presents challenges in enhancing vehicle health monitoring efficiency due to the constrained space for numerous sensing devices, leading to scalability and performance issues. Existing MAC (Medium Access Control) schemes often result in congestion, decreased throughput, and increased delays. This study proposes a scalable hybrid MAC strategy to improve throughput and reduce congestion in IVHMS. The approach features a two-phase communication model—Nonemergency and Emergency phases—for scalability. Our hybrid MAC strategy combines a history-based approach for Emergency Communication and a priority-based approach for Nonemergency Communication. A Markov chain model evaluates the expected throughput and delay of the proposed MAC strategy, with numerical analysis validating the approach. Results show the hybrid MAC achieves a 66.7% throughput improvement over the history-based strategy and a 16.7% improvement over the priority-based approach while effectively reducing data collisions and delays. Furthermore, the hybrid MAC demonstrates an 8.3% increase in throughput compared to a previously proposed distributed hybrid MAC. Implementing this Hybrid MAC in industrial-scale vehicular health monitoring can enhance vehicle safety, benefiting manufacturers and passengers alike. Index Terms—History-based MAC (Medium Access Control), Hybrid MAC, IoT (Internet of Things), Markov chain, Prioritybased MAC, Vehicular Health Monitoring