临床教学

双督导在全科教学门诊中的应用探索

  • 张艳 ,
  • 黄丽娟 ,
  • 朱文华 ,
  • 方力争
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  • 浙江大学医学院附属邵逸夫医院全科医学科,杭州 310016

收稿日期: 2025-01-14

  网络出版日期: 2025-09-02

基金资助

2023年度浙江大学第三临床医学院教学改革研究项目(SYF2023JG17);2025年度浙江省医药卫生科技计划项目(2025KY083)

The construction and practice of the dual-supervision model in general practice teaching clinics

  • Zhang Yan ,
  • Huang Lijuan ,
  • Zhu Wenhua ,
  • Fang Lizheng
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  • Department of General Practice, Sir Run Run Shaw Hospital, Zhejiang University School of Medicine, Hangzhou 310016, China

Received date: 2025-01-14

  Online published: 2025-09-02

Supported by

The Teaching Reform Research Project of the Third Clinical Medical College of Zhejiang University in 2023(SYF2023JG17); The Medical and Health Science and Technology Planning Project of Zhejiang Province in 2025(2025KY083)

摘要

目的 分析双督导在全科教学门诊中的应用效果,为增强全科住院医师岗位胜任力提供参考。方法 2024年1至12月,选取浙江大学医学院附属邵逸夫医院36名全科住院医师与24名基层指导医师开展教学门诊,采用“1名督导医师+1名指导医师+3~5名住院医师”的协同带教模式接诊患者,督导医师负责全程监督教学流程并评估教学质量,指导医师负责门诊带教与技能示范。通过“全科教学门诊接诊评分表”(指导医师评估)和“全科教学门诊指导医师评分表”(督导医师评估)对住院医师接诊能力和指导医师带教能力进行量化评估,同时采用“教学门诊满意度调查问卷”调查督导医师、指导医师、住院医师和患者的满意度。采用t检验和χ2检验分析相关数据。结果 双督导实施后,住院医师的门诊接诊能力评分高于实施前[2022年住院医师:(80.3±3.8)分比(73.6±5.8)分;2023年住院医师:(78.9±2.6)分比(71.3±7.4)分,均P<0.001],合格人数也较前增多[2022年住院医师合格人数从4人增至13人(总人数21人);2023年住院医师合格人数从3人增至7人(总人数15人),均P<0.05]。双督导实施后,指导医师带教能力总分和各维度评分均高于实施前[总分:(75.3±7.7)分比(58.9±6.1)分;带教前准备(满分15分):(12.8±1.8)分比(9.1±1.5)分,教学门诊实施(满分65分):(47.5±5.4)分比(38.6±4.5)分;教学门诊评价(满分20分):(15.3±1.5)分比(11.2±1.4)分,均P<0.001]。督导医师、指导医师、住院医师和患者对教学门诊的满意度均达到100.0%。结论 双督导有助于提升全科住院医师的接诊能力和基层指导医师的教学水平,提升全科住院医师的岗位胜任力,得到了督导医师、指导医师、住院医师和患者的认可。

本文引用格式

张艳 , 黄丽娟 , 朱文华 , 方力争 . 双督导在全科教学门诊中的应用探索[J]. 中华医学教育杂志, 2025 , 45(9) : 681 -685 . DOI: 10.3760/cma.j.cn115259-20250114-00047

Abstract

Objective To analyze the educational impact of the dual-supervision model in general practice teaching clinics and inform enhancing the competency of general practice residents. Methods From January to December 2024, 36 general practice residents and 24 primary care instructors from Sir Run Run Shaw Hospital, Zhejiang University School of Medicine, were enrolled in teaching clinics. A collaborative teaching model (“1 supervising physician + 1 instructor + 3-5 residents”) was implemented, with supervising physicians overseeing the entire teaching process and evaluating teaching quality, while instructors provided clinical mentoring and skill demonstration. The competency of residents and teaching performance of instructors were quantitatively assessed using the General Practice Teaching Clinic Reception Assessment Scale (evaluated by instructors) and the General Practice Teaching Clinic Instructor Evaluation Scale (evaluated by supervising physicians). Satisfaction was surveyed via the Teaching Clinic Satisfaction Questionnaire (anonymous electronic version). Paired t-tests andχ2 tests were used to analyze relevant data. Results After the implementation of the dual- supervision model, the outpatient reception ability score of residents were higher than before [2022 residents: (80.3±3.8) vs. (73.6±5.8); 2023 residents: (78.9±2.6) vs. (71.3±7.4), all P<0.001]. The number of qualified residents significantly increased post-intervention[2022 residents: from 4 to 13 qualified residents (total n=21);2023 residents: from 3 to 7 qualified residents (total n=15),all P<0.05]. After the implementation of the dual-supervision, the total score and various dimensions of the instructors' teaching ability were higher than before implementation: [total score: (75.3 ± 7.7) vs. (58.9 ± 6.1) points; pre-teaching preparation (out of 15 points): (12.8 ± 1.8) vs. (9.1 ± 1.5); teaching implementation (out of 65 points): (47.5 ± 5.4) vs. (38.6 ± 4.5); teaching evaluation (out of 20 points): (15.3 ± 1.5) vs. (11.2 ± 1.4), all P<0.001] . The satisfaction rate of all participants (24 supervising physicians, 24 instructors, 36 residents, 122 patients) reported 100.0%. Conclusions The dual-supervision model effectively enhances residents' clinical competency and instructors' teaching performance, demonstrating high acceptance among all stakeholders. Future efforts should focus on optimizing resource allocation, expanding patient recruitment through community engagement, and integrating online-offline hybrid supervision to maximize scalability.

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