Ward bed resource allocation using data envelopment analysis and a bed workload efficiency model: A case study of a tertiary hospital

Background　Ward bed allocation directly determines both hospital service capacity and operational efficiency. However, existing studies have predominantly focused on the institutional level, often relying on single-indicator analyses that fail to capture the complex input-output efficiency dynamics within individual wards. Objective　To analyze the input-output efficiency of hospital ward resources and provide a reference for ward resource adjustment. Methods　Operational data of 102 wards from a large general tertiary hospital in Beijing were collected from January 1, 2024, to December 31, 2024. Wards were categorized into non-surgical and surgical groups according to department attributes. Both groups shared the same input indicators, while the surgical ward group included the number of patients undergoing Grade Ⅲ and Ⅳ surgeries as an additional output indicator. The BCC model of data envelopment analysis (DEA) was employed to evaluate the input-output efficiency of the two groups, combined with bed efficiency analysis to assess ward bed allocation. Results　Among the 41 non-surgical wards, the mean DEA overall efficiency was 0.900±0.069, the mean pure technical efficiency was 0.917±0.056, and the mean scale efficiency was 0.982±0.058, with 4 wards achieving DEA efficiency. Among the 61 surgical wards, the corresponding values were 0.902±0.113, 0.924±0.088, and 0.974± 0.058, respectively, with 19 wards achieving DEA efficiency. Based on the results of returns to scale analysis and bed efficiency, four bed adjustment strategies were proposed: maintaining the status quo, prioritizing bed expansion, moderately reducing beds, and temporarily deferring adjustment. Conclusion　The integrated DEA and bed efficiency model developed in this study provides a scientific decision-making tool for achieving differentiated bed allocation.