Construction of a classification model for surgical patients and its application in nursing human resource allocation
10.3761/j.issn.0254-1769.2025.15.014
- VernacularTitle:外科手术患者分类模型的构建及在护理人力资源配置中的应用研究
- Author:
Huixia LI
1
;
Lina ZHANG
;
Yinfen JIANG
;
Liping TAN
;
Xuemei ZHANG
;
Juanying HUANG
;
Hui HUANG
;
Xiaojuan TAO
Author Information
1. 215004 苏州市 苏州大学附属第二医院护理部
- Publication Type:Journal Article
- Keywords:
Nursing Workload;
Patient Classification;
Decision Tree;
Human Resource Management;
Nursing Management Research
- From:
Chinese Journal of Nursing
2025;60(15):1884-1891
- CountryChina
- Language:Chinese
-
Abstract:
Objective To construct a classification model for surgical patients and apply it in the allocation of nursing human resources,providing a reference for nursing human resource management.Methods A convenience sampling method was used to retrospectively select 5,431 hospitalized surgical patients admitted to 6 surgical nursing units of a tertiary general hospital in Suzhou from July to November 2022 as the subjects of this study.The nursing hours were measured,and related influencing factors were analyzed.A decision tree classification method was used to establish a classification model for surgical patients.From August to October 2022,1,527 hospitalized surgical patients admitted to 3 nursing units of the same hospital were conveniently selected.The minimum number of nurses required daily was calculated using the surgical patient classification model,actual nursing hours measurement method,nurse-to-bed ratio method,and 8-hour continuous shift scheduling method.The application effect of the surgical patient classification model in nursing human resource allocation was evaluated with the actual nursing hours measurement method as the standard.Results The surgical patient classification model includes 7 classification indicators:length of hospital stay,diagnosis-related group weight,presence or absence of secondary care orders,surgical grade,anesthesia method,age,and presence or absence of critical illness orders.Patients were divided into 14 groups,and the model explained 90.5％of the total variance in nursing workload.The minimum number of nurses required in surgical nursing units calculated based on this model was closest to the result of the actual nursing hours measurement method and was superior to the results of the nurse-to-bed ratio method and the 8-hour continuous shift scheduling method.Conclusion The surgical patient classification model can accurately reflect the nursing workload of such patients.The classification indicators are simple and easy to obtain,and can guide the allocation of human resources in surgical nursing units.
