Abstract: Objective: To explore the application value of Diagnosis Related Groups (DRG) related indicators in nursing workload measurement, aiming to construct a scientific nursing workload evaluation model. Methods: A retrospective analysis was conducted on the data of 11 nursing workload evaluation indicators in 31 departments of a tertiary hospital in Beijing in 2023. The entropy weight method was used to assign weight to each index, and the rank sum ratio method was used to construct DRG and non-DRG workload evaluation models. Compare the advantages and disadvantages of conventional formula, DRG model and non-DRG model for nursing workload evaluation. Results: The weights of the three indicators, namely the number of nurses, the number of discharged patients, and the number of bed turnovers, were the same in both DRG model and non-DRG model. The indicator with the highest weight was the number of transfers in/out, followed by the number of critical patient-days in both models. The relative weight, Case Mix Index (CMI), and In were in the eighth, fifth and tenth position, and CMI value was an important index that cannot be ignored in the model. The department classification results of DRG model and non-DRG model show that there were 5 departments in excellent level (16%), 22 departments in good level (71%), and 4 departments in general level (13%), and the difference in grading results was statistically significant (P<0.05). Conclusion: The workload evaluation model built based on the entropy weight rank and ratio method of DRG related indicators can better reflect the differences among different departments, and has certain reference significance for the measurement of nursing workload, and can provide scientific and effective basis for nursing management decision-making.

Key words: Diagnosis Related Groups; nursing workload; evaluation model; rank-sum ratio; entropy weight method