引用本文:王欣倍,周遨,严晓蕾,张静一,朱琼,王艳,程纯.住院医师规范化培训结业考核专业理论考试结果的影响因素分析[J].中华医学教育探索杂志,2024,23(6):835-840
住院医师规范化培训结业考核专业理论考试结果的影响因素分析
An analysis of factors influencing theoretical graduation examination score of standardized residency training
DOI:10.3760/cma.j.cn116021-20221229-01620
中文关键词:  住院医师规范化培训  通过率  培训质量  影响因素  预测模型
英文关键词:Standardized residency training  Pass rate  Training quality  Influencing factor  Prediction model
基金项目:上海交通大学医学院2021年度毕业后医学教育相关项目(BYH20210408);上海交通大学中国医院发展研究院2019年度医院管理建设项目(CHDI-2019-B-12)
作者单位邮编
王欣倍 上海交通大学医学院附属第九人民医院规范化培训办公室上海 200011 200011
周遨 上海之几信息科技有限公司上海 200071 200071
严晓蕾 上海交通大学医学院附属第九人民医院规范化培训办公室上海 200011 200011
张静一 上海交通大学医学院附属第九人民医院规范化培训办公室上海 200011 200011
朱琼 上海交通大学医学院附属第九人民医院规范化培训办公室上海 200011 200011
王艳 上海交通大学医学院附属第九人民医院院长办公室上海 200011 200011
程纯* 上海交通大学医学院附属第九人民医院规范化培训办公室上海 200011 200011
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中文摘要:
      目的 分析2018至2021年上海某三甲综合医院的住院医师规范化培训(住培)结业考核专业理论考试成绩的影响因素并建立预测模型,为进一步提升住培质量提供参考。方法 收集并整理该基地2018至2021年参加住培结业考核的556名住院医师数据信息,预测分析方法采用二元回归法和逻辑回归模型方法,分别分析住院医师基本信息、住院医师进入基地培训的各类日常考核成绩及反映专业基地培训质量的专业基地绩效考核分数等方面与结业考核专业理论考试成绩的相关性,并构建预测结业考核专业理论考试成绩模型。应用SPSS 26.0进行统计分析,应用二元回归法和逻辑回归法构建模型数据集。结果 2018至2021年该基地共有556人参加住培结业考核,第一站专业理论考站首次合格率为97.48%(542/556),其中双一流学校毕业生一次通过率最高为98.09%(359/366),博士研究生通过率最高为98.59%(140/142),培训两年制的通过率最高为98.34%(297/302)。在住院医师基本信息等分类变量对结业综合考试专业理论考试成绩的影响分析中,使用二元回归法发现专业基地所属级别与住院医师是否通过专业理论的考试有一定相关作用(P<0.05)。在住院医师规培期间的各类日常考核成绩及专业基地绩效考核分数对结业考核专业理论考试成绩(具体分数)的逻辑回归分析中,发现年度专业考核理论成绩、执业医师资格考试首次理论成绩、年度业务水平测试成绩及专业基地绩效考核分数是影响结业考核专业理论考试成绩的关键因素(P<0.05)。结业考专业理论考核成绩的回归分析中,年度业务水平测试成绩回归系数最高,其共线性统计方差扩大因子(variance inflation factor,VIF)也是最高,表明存在较强的多重共线性,因此年度业务水平测试成绩对最终的结业考核专业理论成绩起到较强预测作用。结论 利用二元回归法及逻辑回归模型可分析专业理论考试的可能影响因素及其关联度大小,通过建立的两个住院医师结业考核专业理论考试预测模型,拟预测风险学员。通过贯彻分层递进的理念,增加个性化的辅导等,实现住培信息化管理,智能提前干预,有望进一步提升住培结业考的通过率,最终达到提升住培质量的目的。
英文摘要:
      Objective To analyze the factors influencing the theoretical score of graduation examination of standardized residency training in a class-A tertiary general hospital in Shanghai from 2018 to 2021, and establish prediction models, and to provide a reference for further improving the quality of residency training.Methods We collected the data of 556 residents who participated in the residency training graduation examination at the hospital from 2018 to 2021. Binary regression and logistic regression analyses were used to determine the association of residents' basic information, their routine assessment results at the bases, and the base performance assessment score (indicating the bases' training quality) with theoretical graduation examination results; and prediction models for the theoretical graduation examination score were established, using binary regression and logistic regression methods to construct model datasets. SPSS 26.0 was used for statistical analysis.Results From 2018 to 2021, a total of 556 people participated in the residency training graduation examination at the hospital. The first-time pass rate of the first station theoretical examination station was 97.48% (542/556). Trainees graduating from double first-class schools had the highest first-time pass rate of 98.09% (359/366); doctoral students had the highest first-time pass rate of 98.59% (140/142); and residents of the two-year training program had the highest first-time pass rate of 98.34% (297/302). According to the binary regression analysis of categorical variables such as residents' basic information, the base level was associated with whether residents passed the theoretical examination (P<0.05). According to the logistic regression analysis of residents' routine assessment scores and the base performance assessment score, the annual theoretical assessment score, the first-time theoretical score of the national medical licensing examination, the annual professional performance test score, and the base performance assessment score were key factors affecting the theoretical graduation examination score (P<0.05). In the regression analysis associated with the theoretical graduation examination score, the annual professional performance test score showed the highest regression coefficient and the highest variance inflation factor, indicating strong multicollinearity. Therefore, the annual professional performance test score was important in predicting the theoretical score of the graduation examination.Conclusions This study used binary regression and logistic regression models to analyze the possible factors affecting the theoretical graduation examination score and the degree of association, and also established two prediction models of the theoretical graduation examination score to predict trainees at risk. Through implementing the concept of hierarchical progression, adding personalized tutoring, realizing information management for residency training, and providing intelligent early intervention, the pass rate of residency training graduation examination is expected to be further improved, ultimately achieving the purpose of improving the quality of residency training.
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