首页|基于真实世界数据的大型影像设备资源配置模型的构建与分析

基于真实世界数据的大型影像设备资源配置模型的构建与分析

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  • 万方数据
  • 维普
目的 构建基于真实世界数据(Real World Data,RWD)的计算机断层扫描(Computed Tomography,CT)、磁共振成像(Magnetic Resonance Imaging,MRI)设备的资源配置模型,以优化公立医院大型影像设备的配置问题.方法 选取我院2018年1月至2023年12月医学影像科CT、MRI设备作为研究对象,使用年投资收益率指标分级评价设备的经济效益,然后采用Pearson相关系数法分析医院门诊人次、出院人次、CT/MRI设备检查量与时间的相关性,最后构建基于数据拟合与回归分析的配置预测模型并进行分析评价.结果 CT和MRI设备检查量与住院人次的Pearson相关系数r分别为0.557和0.851(P＜0.01),住院人次、CT和MRI设备检查量与月份的r分别为0.415、0.559和0.731(P＜0.01),相关性强.通过数据拟合与回归分析得到三次配置拟合模型更符合我院实际情况,在未来3年内至少需要增配1台CT和2台MRI设备以顺应医院高速发展需求.结论 构建基于RWD的CT、MRI设备的资源配置模型,有效地优化了大型影像设备的配置规划,为公立医院配置大型影像设备提供决策依据.
Construction and Analysis of Large-Scale Image Equipment Resource Allocation Model Based on Real World Data
Objective To build a resource allocation model of computed tomography(CT)and magnetic resonance imaging(MRI)based on real world data(RWD),in order to optimize the allocation of large-scale image equipment in public hospitals.Methods CT and MRI equipment in the medical imaging department of our hospital from January 2018 to December 2023 were selected as the research objects,and the annual investment return rate was used to grade the economic benefits of the equipment.Then,the Pearson coefficient method was used to analyze the correlation between number of outpatients,discharged patients,total number of CT/MRI equipment examination quantity and time.Finally,a configuration prediction model based on data fitting and regression analysis was constructed.Results The Pearson coefficient r of CT/MRI equipment examination quantity and inpatients were 0.557 and 0.851(P＜0.01),and coefficient of inpatients,CT/MRI examination equipment examination quantity and months were 0.415,0.559 and 0.731(P＜0.01)respectively,which indicated a strong correlation.The three-time configuration fitting model obtained through data fitting and regression analysis was more in line with the actual situation of our hospital.At least one CT and two MRI equipment will be needed to meet the demand of the hospital's rapid development in the next three years.Conclusion The resource allocation model of CT and MRI equipment based on RWD was constructed,which effectively optimizes the configuration planning of large-scale image equipment and provides decision-making basis for public hospitals.

real world data(RWD)large-scale image equipmentresource allocationPearson coefficientfitting and regressioncomputed tomography(CT)magnetic resonance imaging(MRI)

杨明、程时栋、刘洋、朱玉坤、翁飞、田靓

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武汉大学中南医院设备处,湖北武汉 430071

真实世界数据 大型影像设备 资源配置 Pearson相关系数 拟合回归 计算机断层扫描 磁共振成像

湖北省自然科学基金中央高校基本科研业务费专项

2023AFC026413000626

2024

10.3969/j.issn.1674-1633.2024.10.020

中国医疗设备
中国整形美容协会

中国医疗设备

CSTPCD
影响因子：0.825
ISSN：1674-1633
年,卷(期)：2024.39(10)