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提高手术效率:预测泌尿外科手术当天取消的情况

Pablo A Suarez¹, Sudarshan Srirangapatanam², Lynn Leng²

¹University of California, San Francisco, USA. pablo.suarez@ucsf.edu.

World journal of urology

|December 17, 2025

概括

这项研究开发了一种使用电子健康记录和健康的社会决定因素的预测模型,以识别在泌尿器科手术中手术当天取消的高风险患者. 该模型实现了80%的AUC,有助于及时进行手术前干预.

科学领域:

医疗信息学医疗信息学
手术结果研究研究.
预测分析在医疗保健中的应用

背景情况:

手术前一天 (DOS) 的取消会破坏医疗保健效率和患者护理.
早期识别患有DOS取消风险的患者对于有效的术后管理至关重要.
泌尿外科手术容易受到DOS取消的影响,影响资源分配和患者途径.

研究的目的:

在泌尿外科手术中开发和验证DOS取消的预测模型.
将电子健康记录 (EHR) 数据,包括健康的社会决定因素 (SDOH) 整合到预测模型中.
为了识别高风险患者及时进行手术前干预,并降低取消率.

主要方法:

对接受选择性泌尿外科手术的成年患者进行了回顾性队列研究.
利用了包括人口统计,SDOH,临床病史和医疗保健利用在内的EHR数据.
采用激光优化后勤回归用于模型开发和通过交叉验证进行内部验证.

主要成果:

该预测模型为DOS取消预测确定了13个关键变量.
该模型显示曲线下的面积 (AUC) 为0.80,准确度为83%.
在0.4值时,达到81%的灵敏度和55%的特异性,表明强大的预测能力.

结论:

本研究介绍了第一个风险评分模型,集成了全面的SDOH来预测DOS取消.
开发的模型是识别高风险患者和指导手术前干预的新工具.
建议在不同临床场所对模型进行外部验证,以评估可概括性.

关键词:

健康上的不平等卫生上的不平等医疗服务的可访问性没有出现的患者.健康的社会决定因素泌尿外科手术的手术程序.

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