[1]沈鑫陈航黄波杨江存.输血辅助决策系统构建与应用效果分析[J].中国卫生质量管理,2021,28(08):073-76.[doi:10.13912/j.cnki.chqm.2021.28.8.19 ]
　SHEN Xin,CHEN Hang,HUANG Bo.Construction and Effect Analysis of Blood Transfusion Decision-Making Supporting System[J].Chinese Health Quality Management,2021,28(08):073-76.[doi:10.13912/j.cnki.chqm.2021.28.8.19 ]
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输血辅助决策系统构建与应用效果分析
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《中国卫生质量管理》[ISSN:1006-7515/CN:CN 61-1283/R]

卷:
第28卷
期数:
2021年08期
页码:
073-76
栏目:
血液质量
出版日期:
2021-08-28

文章信息/Info

Title:
Construction and Effect Analysis of Blood Transfusion Decision-Making Supporting System
作者:
沈鑫陈航黄波杨江存
陕西省人民医院
Author(s):
SHEN Xin; CHEN Hang; HUANG Bo
Shaanxi Provincial People's Hospital
关键词:
输血辅助决策系统; 智慧医疗; 临床用血; 精准用血; 红细胞输注
Keywords:
Blood Transfusion Decision-Making Supporting System;  Wisdom Medical Care;  Clinical Use of Blood;  Accurate Use of Blood;  Red Blood Cell Infusion
分类号:
R197.3;R331.1
DOI:
10.13912/j.cnki.chqm.2021.28.8.19
文献标志码:
B
摘要:
采集医院HIS、LIS、输血管理平台、手术麻醉管理等系统中申请用血、发血、用血相关数据，采用自然语言处理、数据挖掘清洗方式生成用血信息数据库，基于循环神经网络及贝叶斯算法等机器学习构建用血智能评估模型，通过临床红细胞输注前后效果评估、历史用血数据对模型验证修订反馈，不断完善。初步建立了精准、有效的红细胞输注辅助决策系统，该系统可为临床医师提供红细胞输注决策建议，指导临床合理用血，实现精准用血管理。
Abstract:
Data related to blood application, blood delivery and blood consumption were collected from the electronic medical record of hospital information system (HIS), laboratory information system (LIS), blood transfusion management platform and surgical anesthesia management system. The blood information database was generated by natural language processing, data mining and cleaning methods. An intelligent evaluation model of blood consumption was built based on machine learning such as circulating neural network and Bayesian algorithm. The model was continuously improved through the effect evaluation before and after clinical red blood cell infusion and the verification and revision feedback of historical blood data. An accurate and effective decision-making system for red blood cell infusion had been established. The system can provide clinicians with red blood cell transfusion decision suggestions, guide clinical rational blood use, and achieve accurate blood use management.

参考文献/References:

［1］唐吉伟德.建立无偿献血志愿队应对血荒具有破题之效［EB/OL］.（2019-03-15）［2020-02-29］.http://view.k618.cn/rmpl/201903/t20190315_17267031.htm. ［2］Jo C，Ko S，Shin WC，et al.Transfusion after total knee arthroplasty can be predicted using the machinelearning algorithm［J］.Knee Surg Sports Traumatol Arthrosc，2019，7（28）：1-8. ［3］李 杰，段光友，曾 义，等.人工神经网络、极端梯度提升和Logistic回归用于预测再次剖宫产术中输血的比较分析［J］．第三军医大学学报，2019，41（24）：2430-2437. ［4］沈 鑫，常建华，石斌娅，等.基于闭环输血信息管理平台的临床用血管理［J］．中国卫生质量管理，2018，25（2）：108-110.

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更新日期/Last Update: 2021-08-28