Efficiency analysis and management strategies of hospital beds based on diagnosis-related groups / 中华医院管理杂志
Chinese Journal of Hospital Administration
; (12): 201-205, 2023.
Article
in Zh
| WPRIM
| ID: wpr-996061
Responsible library:
WPRO
ABSTRACT
Objective:To improve the evaluation method of hospital beds efficiency based on diagnosis-related groups (DRG), and to provide a basis for hospitals to allocate beds reasonably and improve bed efficiency.Methods:Taking a tertiary hospital in Beijing as the research object, the types of beds were evaluated by the beds utilization matrix with the time consumption index as the X-axis and the bed utilization rate as the Y-axis. The types of beds in the department were divided into efficiency type, pressure type, turnover type, and idle type. The efficiency of medical services and the level of diagnosis and treatment were evaluated by the weight of DRG per bed. The calculation method of theoretical number of beds was improved by incorporating hospital case mix index as a risk adjustment factor into the formula to evaluate the status of beds allocation. Combining the bed type, DRG weight per bed, and bed allocation status, the improvement emphasis and management strategy of bed utilization could be comprehensively analyzed.Results:Among the 24 departments in the hospital, there were 5, 9, 1 and 9 departments being efficiency type, pressure type, turnover type and idle type, respectively. The weight per bed of 11 departments was higher than the average level of the hospital. There were 16, 5, and 3 departments with appropriate, fewer, and excessive beds, respectively.Conclusions:The comprehensive analysis of beds utilization type, allocation status and weight of each bed based on DRG is an effective method to evaluate the efficiency of hospital beds, and can provide decision-making basis for hospital bed resource allocation, hospital operation focus adjustment, and subject development planning.
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Index:
WPRIM
Language:
Zh
Journal:
Chinese Journal of Hospital Administration
Year:
2023
Type:
Article