AUTHOR=Wang Waner , Li Gege , Pu Jiangfeng , Shen Tiemei , Xie Zhanghao , Chen Lifang , Cui Hong , Xu Peng , Huang Huigen 

TITLE=A Delphi-based framework for optimizing nurse staffing in Chinese hospitals

JOURNAL=Frontiers in Public Health

VOLUME=Volume 13 - 2025

YEAR=2025

URL=https://www.frontiersin.org/journals/public-health/articles/10.3389/fpubh.2025.1510931

DOI=10.3389/fpubh.2025.1510931

ISSN=2296-2565

ABSTRACT=ObjectiveThe objective of this study was to develop an evaluation system for the allocation of hospital nursing human resources in hospitals in the context of the Healthy China initiative.AimsThe evaluation system aims to provide a foundation and recommendations for optimizing the allocation of hospital nursing human resources by providing data-driven insights to guide staffing decisions. These recommendations are designed to enhance patient safety, reduce adverse events, and improve overall nursing care quality while supporting the sustainable development of healthcare systems. The system also seeks to enhance nursing human resource management by enabling managers to allocate resources more effectively based on clinical workload, patient needs, and nursing competencies. The primary objectives of this optimization process include reducing nurse workload, improving job satisfaction, and decreasing turnover rates, all of which facilitate improved patient outcomes.MethodsThe evaluation index pool and questionnaire for the index system consultation were developed using a literature review and semi-structured expert interviews. Considering the need for detailed information on the number of experts and the criteria for indicator deletion, we clarified that the study included 26 experts. These experts were selected based on their extensive experience and professional background in nursing management. The criteria for indicator deletion included a variation coefficient of >0.25 and expert consensus on the relevance and importance of the indicators. We conducted two rounds of expert consultations using the Delphi method to screen the evaluation indexes. Subsequently, the weights of the indexes were calculated using the analytic hierarchy process (AHP).ResultsA nursing human resource staffing evaluation system was established, comprising 3 primary indexes, 7 secondary indexes, and 25 tertiary indexes.ConclusionThe findings of this study provide empirical evidence and specific recommendations for evaluating, guiding, incentivizing, and improving nursing human resource management practices in China. This study is the first structured Delphi-and AHP-based staffing evaluation system in a Chinese hospital setting. By integrating expert consensus and hierarchical analysis, we have developed a novel framework tailored to China’s healthcare needs. This framework significantly contributes to the integrated development of nursing human resource management. Based on the results, we recommend that hospitals implement the evaluation system to regularly monitor and optimize their nursing staffing levels. Moreover, further research may help explore the long-term effects of this system on patient outcomes and nurse retention rates across different hospital settings. Future studies may also examine the adaptability of the evaluation system to various specialties and the potential need for adjustments in specific contexts.