Posted: Aug 05, 2024
This research presents a novel computational framework for analyzing the complex role of nurse leaders in healthcare organizational change during systemic reforms. Unlike traditional qualitative approaches in healthcare leadership studies, we developed a multi-agent simulation system that models the intricate dynamics between nurse leaders, clinical staff, administrative systems, and policy implementation processes. Our methodology integrates principles from complex adaptive systems theory with machine learning techniques to create a virtual healthcare environment where leadership interventions can be tested and optimized. The simulation incorporates realistic constraints including resource limitations, staff resistance to change, regulatory requirements, and patient care quality metrics. Through extensive computational experiments, we identified three previously undocumented leadership patterns that significantly accelerate successful reform implementation: adaptive resonance communication, distributed decision-making cascades, and resilience-based resource allocation. Our findings demonstrate that nurse leaders who employ these patterns achieve 47
Downloads: 33
Abstract Views: 1304
Rank: 468946