摘要
目的预测医疗护理资源需求,实现医护资源最优管理。方法对海量医护数据进行分析和统计,利用近邻域思想提取数据特征及训练样本集;结合人工智能领域的支持向量机(SVM)算法建立医护资源调配的数学模型;依赖新的数学模型,医护管理人员可以对未来可能发生的医护资源需求进行预测以优化资源调配方案。根据建立的数学模型,对本院5个科室的历史数据进行分析建模,得到预测结果。结果预测结果表明基于数据驱动的新型医护资源调配模型在历史数据驱动下能有效预测未来的医疗护理资源需求,5个科室中预测准确率为92%~94%,平均预测准确率达93%。结论基于数据驱动的医疗护理资源管理在现代医院中具有广泛的应用前景,在提高护理管理水平方面能发挥重要作用,为实现智能医院探明方向。
Objective To predict the demand of medical care resources,and to realize optimal management of medical care resources.Methods The mass data of medical care resources were analyzed and counted,and the data characteristics and training sample sets were extracted using near neighborhood thinking.The mathematical model of health care resource allocation was established by combining the support vector machine（SVM）algorithm in artificial intelligence.Depending on the new mathematical model,health care managers can predict the requirement of medical care resources to propose an optimal allocation scheme of medical care resources.According to the established mathematical model,the historical data of 5 departments in the hospital were analyzed and modeled,and the prediction results were obtained.Results The prediction results showed that the new model of health care resource allocation based on data driven could effectively predict future medical care resources demand driven by historical data.The accuracy rate of the 5 departments was 92%-94%,and the average prediction accuracy rate was 93%.Conclusion Medical care resource management based on data driven has a broad application prospect in modern hospitals,and it plays an important role in improving the level of nursing management,so as to explore the direction for realizing intelligent hospital.
作者
袁丽洁
李敏
雷涛
Yuan Lijie, Li Min, Lei Tao.(Medical Department, Shaanxi Provincial People′s Hospital, Xi′an 710068,Chin)
出处
《护理学杂志》
CSCD
北大核心
2018年第15期55-58,共4页
Journal of Nursing Science
基金
国家自然科学基金项目(61461025)
关键词
医疗护理
资源管理
数学模型
大数据
支持向量机
训练样本
medical care
resource management
mathematical model
big data
support vector machine
training samples
