Analysis on teaching ward round supervision of residency standardized training based on user portrait

  • Yan Yanhong ,
  • Liu Tuo ,
  • Li Xuan
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  • 1Department of Science and Education, The Third People′s Hospital of Chengdu & The Affiliated Hospital of Southwest Jiaotong University, Chengdu 610031, China;
    2National Institute for Occupational Health and Poison Control, Chinese Center for Disease Control and Prevention, Beijing 100050, China;
    3The Third People′s Hospital of Chengdu & The Affiliated Hospital of Southwest Jiaotong University, Chengdu 610031, China

Received date: 2022-12-23

  Online published: 2023-11-27

Supported by

Scientific Research Project of Health Commission of Sichuan Province(19PJ014); Sichuan Philosophy and Social Sciences Aging Research Center (XJLL2019014); Scientific Research Project of Sichuan Medical Association (S20082)

Abstract

Objective To analyze the problems of teaching ward round supervision in a standardized training base for residency, and provide reference for improving the teaching quality of the standardized training base for residency. Methods Results of the teaching ward rounds of the 93 supervising physicians in the standardized training base in the southwest China from April 2021 to August 2022 were collected, and descriptive statistical analysis and K-means clustering was used. Results Among the 93 supervising physicians,33(35.5%)supervising physicians were insufficient use of foreign words,24(25.8%)supervising physicians were insufficient item preparation of ward round, and21(22.6%)supervising physicians were insufficient interaction and unreasonable time allocation. It was showed by cluster analysis that the main problems of supervising physicians with intermediate titles were inappropriate clinical cases, unfamiliar with the case conditions and insufficient teaching ability; the problems of the supervising physicians with associate senior titles were mainly in the deficiencies of analysis the examination report, writing comments on medical records, guiding differential diagnosis and treatment plan; the main problems of supervising physicians with senior titles were insufficient questions & answers. Conclusions The main problems in the teaching ward round supervision for residency standardized training included insufficient use of foreign words, insufficient item preparation of ward round, and insufficient interaction and unreasonable time allocation. There were different problems in supervising physicians with different titles. It was suggested that targeted measures should be adopted to improve their teaching ability at different levels.

Cite this article

Yan Yanhong , Liu Tuo , Li Xuan . Analysis on teaching ward round supervision of residency standardized training based on user portrait[J]. Chinese Journal of Medical Education, 2023 , 43(12) : 938 -941 . DOI: 10.3760/cma.j.cn115259-20221223-01580

References

[1] 丁敏,孙晓靓,罗茜,等. 住院医师规范化培训全程导师智能管理系统的应用效果分析[J]. 中华医学教育杂志,2023,43(3):218-221. DOI:10.3760/cma.j.cn115259-20220723-00931.
[2] 吴硕,简非同. 思维导图在住院医师规范化培训耳鼻咽喉头颈外科临床教学查房中的应用[J]. 中华医学教育杂志,2022,42(8):740-743. DOI:10.3760/cma.j.cn115259-20220202-00131.
[3] 向军,徐莉莉,蔡敏,等. 中医住院医师规范化培训研究的可视化分析[J]. 中华医学教育杂志,2023,43(4):303-306. DOI:10.3760/cma.j.cn115259-20220610-00762.
[4] 丁敏, 罗茜, 孙晓靓, 等. 住院医师规范化培训质量控制体系[J].解放军医院管理杂志,2021,28(7):686-689. DOI: 10.16770/J.cnki.1008-9985.2021.07.029.
[5] 严飞,柴栖晨,吕晶,等. 全科医学专业住院医师规范化培训学员对缓和医疗的认知和培训需求调查[J]. 中华医学教育杂志,2023,43(7):539-542. DOI:10.3760/cma.j.cn115259-20221002-01252.
[6] 王广辉,朱晓燕,周全,等. 住院医师规范化培训质量评估[J]. 解放军医院管理杂志,2018,25(1):56-59.
[7] 费晓璐, 马丽平, 尉俊铮, 等. 基于真实世界数据的中心静脉输注工具评价及应用[J].中国医院管理,2021,41(4):60-64.
[8] 尤明辉, 殷亚凤, 谢磊, 等. 基于行为感知的用户画像技术[J].浙江大学学报(工学版),2021,55(4):608-614,638. DOI: 10.3785/j.issn.1008-973X.2021.04.002.
[9] 张海涛, 栾宇, 周红磊. 用户画像:向知识迈进[J].图书情报知识,2020(5):131-134. DOI: 10.13366/j.dik.2020.05.122.
[10] Sun Z, Xu L, Zhong Q, et al. Chinese App user′s needs profile: from questionnaire measurement to behavior analysis[J]. Front Psychol, 2021,12:655612. DOI: 10.3389/fpsyg.2021.655612.
[11] Sharma S, Gupta V. Role of twitter user profile features in retweet prediction for big data streams[J]. Multimed Tools Appl, 2022,81(19):27309-27338. DOI: 10.1007/s11042-022-12815-1.
[12] Fiorini L, Coviello L, Sorrentino A, et al. User profiling to enhance clinical assessment and human-robot interaction: a feasibility study[J]. Int J Soc Robot, 2023,15(3):501-516. DOI: 10.1007/s12369-022-00901-1.
[13] 陈默, 蔡苗, 黄阿红, 等. 基于K-means聚类与支持向量机的大病患者住院费用影响因素与控制策略研究[J].中国医院管理,2019,39(5):45-47,53.
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