基于数据挖掘的大型医疗设备配置预测模型建立与评估  

Establishment and Evaluation of Large-scale Medical Equipment Configuration Prediction Model Based on Data Mining

作　　者：朱伟 方舸 严郁 ZHU Wei;FANG Ge;YAN Yu(Department of Equipment,Affiliated Hospital Nanjing University of Chinese Medicine(Jiangsu Province Hospital of Chinese Medicine),Nanjing Jiangsu 210029,China)

机构地区：[1]南京中医药大学附属医院(江苏省中医院)设备处,江苏南京210029

出　　处：《中国医疗设备》2020年第12期63-66,共4页China Medical Devices

摘　　要：目的为进一步解决大型医疗设备合理配置的问题,以CT为例建立医疗设备配置预测模型。方法首先采用投资回报法评价CT的经济效益,然后使用皮尔逊系数分析医院门诊量、CT检查量及时间的相关性,最后利用回归分析法建立预测模型并进行评价。结果CT检查量与全院门诊量的皮尔逊相关系数为0.797(P<0.001),高度线性相关。根据预测模型(y=-0.51t2+184.2t+9166.5),未来5年内至少需要增加3台CT才能满足医院的CT检查最低需求。结论通过挖掘医院数据,建立大型医疗设备配置预测模型,为医院合理编制预算提供决策依据。Objective To solve the problem of rational allocation of large-scale medical equipment,CT was taken as an example to establish a prediction model of medical equipment configuration.Methods Firstly,the economic benefit of CT was evaluated by the return on investment method.Then,Pearson coefficient was used to analyze the correlation between the hospital outpatient quantity,the CT examination quantity and time in hospital.Finally,regression analysis method was used to establish the prediction model.Results The Pearson’s correlation coefficient between the CT examination quantity and the hospital outpatient quantity was 0.797(P<0.001),which was highly linear.According to the prediction model(y=-0.51t2+184.2t+9166.5)at least 3 additional CTs will be needed to meet the minimum requirements for CT examinations within the next 5 years.Conclusion By mining the hospital data,a large-scale medical equipment configuration prediction model is established to provide a decision-making basis for the hospital’s reasonable budget.

关 键 词：大型医疗设备 数据挖掘 相关性 回归分析 

分 类 号：R197.39[医药卫生—卫生事业管理]