Objective Itproposes a WISN staffing demand model for clinical physicians to address the challenge that current physicians staffing standards fail to meet the operational needs of general hospitals.Methods Collect the 2023 annual operation data of a tertiary general hospital,using inpatient visits and surgeries as benchmarks to measure the workload demands of physicians in internal medicine and surgery,respectively.Additionally,integrate non-clinical workloads of physicians and the workload of resident physicians in standardized training to address the limitation of traditional models that focus solely on clinical tasks.Results The good applicability and robustness of the model in practical applications are verified through model comparison and sensitivity analysis,accurately reflecting the demand for physicians.Conclusion The model accurately reflects the workload of physicians in general hospitals,providing a quantitative estimation formula for physicians staffing.It has broad applicability and significant potential for wider adoption.

Objective Itproposes a WISN staffing demand model for clinical physicians to address the challenge that current physicians staffing standards fail to meet the operational needs of general hospitals.Methods Collect the 2023 annual operation data of a tertiary general hospital,using inpatient visits and surgeries as benchmarks to measure the workload demands of physicians in internal medicine and surgery,respectively.Additionally,integrate non-clinical workloads of physicians and the workload of resident physicians in standardized training to address the limitation of traditional models that focus solely on clinical tasks.Results The good applicability and robustness of the model in practical applications are verified through model comparison and sensitivity analysis,accurately reflecting the demand for physicians.Conclusion The model accurately reflects the workload of physicians in general hospitals,providing a quantitative estimation formula for physicians staffing.It has broad applicability and significant potential for wider adoption.