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基于大数据病种组合的价格形成研究 被引量:4

Research on price-formation in the big data diagnosis-intervention packet
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摘要 目的:探讨基于大数据病种组合的价格形成方法和价格标准。方法:使用2018年上海市95家医疗机构的支出数据和收入数据进行分析,其中市级医院33家,区级医院62家。使用病种分值标化数据后,以每指数单价和每指数成本的区域均值为坐标轴将区域内的医疗机构划分为4个象限;寻找出收入和成本最优的象限,即优质区间;在优质区间求出几何中心,并以该几何中心的每指数单价作为费用标准。结果:上海市区级医院的收支分布情况为:第一象限20家,第二象限8家,第三象限24家,第四象限10家;市级医院位于第一象限7家,第二象限5家,第三象限12家,第四象限9家。第三象限医疗机构的平均收入和成本均低于全市均值,且收入能够覆盖成本,为优质区间。区级医院第三象限几何中心的每指数单价为14115.4元,市级医院为15559.1元,可作为相应的费用标准。结论:基于客观数据及优质区间几何中心法的价格发现机制,能去除不合理收费或不合理行为对医疗收入的影响,体现医保支付标准价格的导向性。 Objective To explore the price formation method and price standard in the big data diagnosis-intervention packet.Methods The expenditure data and income data of 95 medical institutions in Shanghai in 2018 were used for analysis,including 33 municipal hospitals and 62 district hospitals.After using the standardized data of disease score,the medical institutions in the region were divided into four quadrants with the regional average of unit price per index and cost per index as the coordinate axis.The best quadrant of income and cost was found out,namely the high quality range.The geometric center was calculated in the high quality range,and the unit price per index of the geometric center was taken as the cost standard.Results For the district hospitals,there were 20 hospitals in the first quadrant,8 in the second quadrant,24 in the third quadrant and 10 in the fourth quadrant;For the municipal hospitals,there were 7 hospitals in the first quadrant,5 in the second quadrant,12 in the third quadrant and 9 in the fourth quadrant.In the third quadrant,the average income and cost of medical institutions were lower than the average of the city,and the income could cover the cost.The third quadrant was the high quality range.The unit price per index of the third quadrant geometric center of district hospitals was 14115.4 yuan,and that in municipal hospitals was 15559.1 yuan,which could be used as the corresponding cost standard.Conclusions The price discovery mechanism based on objective data and high-quality interval geometric center method can remove the impact of unreasonable charges or unreasonable behavior on medical income,and reflect the guidance of the standard price of medical insurance payment.
作者 杨羽佳 邬惊雷 谢桦 汪森然 崔欣 宣建伟 许速 Yang Yujia;Wu Jinglei;Xie Hua;Wang Senran;Cui Xin;Xuan Jianwei;Xu Su(Shanghai Information Center for Health,Shanghai 200040,China;Shanghai Municipal Health Commission,Shanghai 200125,China;Wonders Information Co.,Ltd.,Shanghai 200040,China;School of Pharmaceutical Sciences,Sun Yat-Sen University,Guangzhou 510275,China)
出处 《中华医院管理杂志》 CSCD 北大核心 2021年第3期191-195,共5页 Chinese Journal of Hospital Administration
基金 国家重点研发计划重点专项(2016YFC1305605) 国家自然科学基金(71003024) 上海市卫生健康委员会政策研究课题(2020HP17)。
关键词 大数据 病种分值付费 价格形成机制 费用标准 几何中心 Big data Diagnosis-intervention packet Price-formation mechanism Charge standard Geometric center
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