基于医疗大数据的手术分级探索与实践

Exploration and Practice of Operation Classification Based on Medical Big Data

根据平均总费用、平均手术费用、平均手术成本、平均手术时间、平均手术人员、次要诊断平均个数、手术死亡率、平均住院日、平均术后住院日等9大指标,以2017年产生的医疗大数据,测算各级手术的难度系数,对同级别手术难度全面量化,将顺序数据转变为数值型数据,且动态调整,构建了一套可量化、可推广、符合实际的手术难度系数评价系统,激发了临床医师参与手术分级实践的积极性,推动了手术分级绩效管理的开展。

According to the medical big data generated by the hospital in 2017,the comprehensive classification of operative difficulty was explored based on nine index of average total cost,average operation expense,average operation cost,average operation time,average operation personnel,average number of secondary diagnoses,operative mortality,average hospital stay,and average postoperative hospital stay.The difficulty coefficient of all levels of operation,and comprehensively quantify the difficulty of the same level of operation were measured,followed by converting the sequence data into numerical data with dynamic adjustment.A quantifiable,scalable and practical evaluation system of surgical difficulty coefficient was established,which stimulated the enthusiasm of clinical participation in operation classification practice and promoted the development of operation classification performance management.