Node impact in networks is important for information transmission, pandemic prevention, and infrastructure resilience. Different centrality measures help understand node significance, but they may not capture both local and global influence efficiently. A new measure called Isolating-Betweenness Centrality (ISBC) combines Betweenness Centrality and Isolating Centrality to evaluate node impact. ISBC outperforms other centrality measures in spreading efficiency on real-world datasets, showing improved performance with moderate time complexity.