The assessment of Health Services and Support Equipment Systems effectiveness using simulation evaluation methods involves several complex steps, including scenario configuration, multiple simulation system runs, and the invocation of effectiveness evaluation models. To address the issues of process complexity and time consumption, this paper proposes a weapon system of systems effectiveness evaluation method based on a quantum-classical hybrid deep neural network (QCH-DNN). This approach integrates quantum computing with classical deep learning strategies by merging quantum circuit design with fully connected neural network layers to construct a hybrid model. Experiments conducted using multiple datasets yielded performance-optimized output results, preliminarily validating the effectiveness and practical value of the proposed method. The results demonstrate that this method significantly improves evaluation efficiency and accuracy.