Cloud computing has revolutionized healthcare data management, leading to better patient care. Most healthcare organizations now use cloud-based software and related services to provide superior healthcare facilities. The primary goals of fog computing are to address the issues of cloud computing’s energy usage, network latency, and bandwidth. Managing data generated by healthcare IoT devices is another important application of fog computing. Data generated by healthcare IoT devices is enormous and requires efficient processing with low latency, zero failures, low energy consumption, and low cost. Hence this paper, Fog Computing based Fault Tolerant Data Management Model (FC-FTDMM), has been proposed for healthcare data management. Processing and encrypting the collected physiological signals are done using the Advanced Secured Encryption Algorithm (ASEA) before its transmission to the cloud. Healthcare IoT device data is structured and handled effectively in FC-FTDMM using well-defined components and stages. FTDM provides a two-way fault-tolerant mechanism for tasks and node failures: task-based and node-based fault tolerance. The findings display the FC-FTDMM for performance assessment data management ratio of 92.1% and 93.2%, latency of 0.21 ms and 0.2 ms, and decision-making ratio of 96.5% compared to other methods.