Optimizing Patient Distribution Through the Adaptation of the RAFAELA System by Strengthening the Role of Nurse Unit Managers to Achieve Equitable Nursing Workload Distribution

Vollständiger Abstract

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Increasing patient complexity and Bed Occupancy Rate (BOR) have contributed to higher nursing workload at X hospital. These conditions potentially lead to imbalanced workload distribution, nurse fatigue, and decreased quality of care and patient safety. This study aimed to optimize competency-based nurse staffing through the role of Nurse Unit Managers (NUMs) in managing nursing workload at X hospital. This study used a project improvement approach conducted during nursing management residency activities in inpatient units on the 5th, 10th, 11th, 12th, and 13th floors of X hospital from April to May 2026. Data were collected through observations, semi-structured interviews, and document reviews. Problem analysis was conducted using the POSAC approach and fishbone analysis. The intervention was implemented through competency-based staffing using the RAFAELA System as a nursing intensity measurement tool. Most patients had partial to total dependency levels with high clinical complexity. The nurse-to-patient ratio increased to 1:9–11 during full BOR conditions. Patient assignment was previously based on room location rather than patient complexity and nurses’ competency levels, resulting in workload imbalance. The implementation of competency-based staffing assisted NUMs in distributing patients more objectively according to patient complexity and nurses’ competencies. Competency-based nurse staffing optimization through strengthening the role of NUMs and utilization of the RAFAELA System has the potential to improve nursing service effectiveness, support patient safety, and create more proportional workload distribution.