Impact of a Dynamic Nurse-to-Patient Ratio Policy in the ICU: a Hybrid Simulation Model

Abstract

Nurse staffing levels play a crucial role in ensuring high-quality patient care, particularly in intensive care settings. This study evaluates the impact of a proposed nurse-to-patient ratio policy on patient outcomes, nurse workload, and ICU efficiency in hospitals. Using a hybrid simulation approach integrating Discrete Event Simulation and Agent-Based Modeling, the study compares the effects of a fixed 1:2 ratio (current policy) with a dynamic, acuity-based ratio (proposed policy). Findings indicate that adaptive staffing improves emergency response times, reduces nurse burnout, and enhances overall quality of care. Results demonstrate that a flexible approach to staffing allocation leads to better workload distribution and resource utilization. By providing an evidence-based evaluation of nurse-to-patient ratios, this study supports policy discussions on staffing optimization in resource-limited healthcare systems. These findings highlight the need for dynamic workforce management to improve patient care while maintaining operational efficiency in ICUs.