[1]邢晨伟王清江盛伟琪.基于多层神经网络算法的主诊医师岗位核定研究[J].中国卫生质量管理,2022,29(04):046-49.[doi:10.13912/j.cnki.chqm.2022.29.4.13 ]
 XING Chenwei,WANG Qingjiang,SHENG Weiqi.Post Verification of Attending Physician Based on Multilayer Neural Network Algorithm[J].Chinese Health Quality Management,2022,29(04):046-49.[doi:10.13912/j.cnki.chqm.2022.29.4.13 ]
点击复制

基于多层神经网络算法的主诊医师岗位核定研究
分享到:

《中国卫生质量管理》[ISSN:1006-7515/CN:CN 61-1283/R]

卷:
第29卷
期数:
2022年04期
页码:
046-49
栏目:
医疗质量
出版日期:
2022-04-28

文章信息/Info

Title:
Post Verification of Attending Physician Based on Multilayer Neural Network Algorithm
作者:
邢晨伟王清江盛伟琪
复旦大学附属肿瘤医院/复旦大学上海医学院肿瘤学系
Author(s):
XING ChenweiWANG QingjiangSHENG Weiqi
Fudan University Shanghai Cancer Center/Department of Oncology,Shanghai Medical College Fudan University
关键词:
多层神经网络算法主诊医师岗位核定
Keywords:
Multilayer Neural Network Algorithm Attending Physician Post Verification
分类号:
R197.32
DOI:
10.13912/j.cnki.chqm.2022.29.4.13
文献标志码:
B
摘要:
目的探索主诊医师岗位核定的科学方法。方法多层神经网络算法。结果3个主诊医师岗位核定影响因素的标准化重要性排序从高到低依次为:床位数(100.0%)、年床均出院量(10.1%)、三四级手术占比(9.3%),并精准预测了各外科科室主诊医师岗位数,外科医师对主诊医师岗位核定方案满意,总体满意度得分为(4.40±0.31)分。结论运用多层神经网络算法科学设置主诊医师岗位数,能够充分调动医生主观能动性,有利于医疗资源合理配置。
Abstract:
ObjectiveTo explore the scientific method of post verification of attending physician. MethodsThe multilayer neural network algorithm was used.ResultsThe standardized importance of the three factors,ranked from high to low: the number of beds (100.0%), the annual discharge per bed (10.1%), and the proportion of third-grade and fourth-grade operations (9.3%). The number of posts of attending physicians in each surgical department was accurately predicted. Surgeons were satisfied with the post verification scheme of attending physicians, and the overall satisfaction score was (4.40±0.31) points.Conclusion The use of multilayer neural network algorithm to scientifically set the number of attending physician can fully mobilize the subjective initiative of doctors, which is conducive to the rational allocation of medical resources.

参考文献/References:

[1]周丹青,张戟,杨佳芳,等.某院床位带组医生岗位核定研究[J].中国卫生质量管理,2018,25(6):47-49. [2]刘文生.打造主诊医师制全新样板[J].中国医院院长,2018(10):52-57. [3]何安南,鲁胜锟,邬姜海.主诊医师负责制的矩阵组织管理模式提升医疗质量[J].世界最新医学信息文摘,2017,17(A3):12-13,16. [4]吴少玮,孙晖.主诊医师负责制下某医院临床科室医疗组现状与分析[J].中国医院管理,2019,39(7):34-35. [5]徐僖,胡馨予,钱翠玉,等.主诊医师负责制的实践与探讨[J].医院管理论坛,2020,37(7):36-37,53. [6]周昀,程永忠,李为民.四川大学华西医院主诊医师负责制的探索与实践[J].中国卫生事业管理,2018,35(11):816-818. [7]侯天春,吴正一,崔迎慧,等. 基于Ridit和RSR法的临床手术科室风险系数及其风险等级评价[J].中国医院管理,2021,41(1):48-51,62. [8]王鑫,刘金亮,周舸,等. Ti-6Al-4V合金超塑性变形行为的人工神经网络预测[J].沈阳工业大学学报,2021,43(2):163-168. [9]绳慧峰,刘晴,许苹,等.人工神经网络在医疗风险预测中的应用研究[J].中国卫生质量管理,2017,24(4):15-17. [10]祁春阳. 基于多层神经网络的人员室内运动状态识别方法研究[D].徐州:中国矿业大学,2018. [11]王雪云,周学健,王方方.浅析医院核心制度下推行主诊医师负责制的问题与建议[J].现代医院管理,2021,19(4):60-63.

相似文献/References:

[1]王颖倩 汤小波 何纪毅 陈翀 张文砚 吴巍巍 郭明和 杨锦锦 武剑.基于DRGs平台的主诊医师团队医疗质量评价研究[J].中国卫生质量管理,2019,26(02):036.[doi:10.13912/j.cnki.chqm.2019.26.2.12]

更新日期/Last Update: 2022-04-28