Volume 22 Issue 9
Sep.  2024
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Article Navigation >  Chinese Journal of General Practice  > 2024  >  22(9): 1592-1595
JIA Jian, GAO Wen, CHENG Hongyan, XU Zhiyang, ZHAN Yiyang. Research on the training of primary medical care personnel based on CBL data model in Jiangsu Province[J]. Chinese Journal of General Practice, 2024, 22(9): 1592-1595. doi: 10.16766/j.cnki.issn.1674-4152.003690
Citation: JIA Jian, GAO Wen, CHENG Hongyan, XU Zhiyang, ZHAN Yiyang. Research on the training of primary medical care personnel based on CBL data model in Jiangsu Province[J]. Chinese Journal of General Practice, 2024, 22(9): 1592-1595. doi: 10.16766/j.cnki.issn.1674-4152.003690
shu

Research on the training of primary medical care personnel based on CBL data model in Jiangsu Province

doi: 10.16766/j.cnki.issn.1674-4152.003690
  • 1.

    General Practice Department, the First Affiliated Hospital of Nanjing Medical University, Nanjing, Jiangsu 210029, China

Funds:

 2021JSJY030

 2020A01

  • Received Date: 2023-05-13
    Abstract
  •   Objective  To explore a new way to improve the training effect of primary medical care personnel (PMCP) in Jiangsu Province based on the application of a case based learning (CBL) data model.  Methods  A total of 123 PMCP from 5 cities (including Nanjing, Suzhou, Wuxi, Suqian and Yancheng) in Jiangsu Province were selected as subjects from January to June in 2022. The clinical case database based on the CBL data model was used for online training, and the test of clinical knowledge structure was conducted before and after the training. T-test and one-way ANOVA were used to analyze the difference in PMCP ability. Multiple linear regression was used to analyze the factors affecting the training effect.  Results  The mean scores of 123 PMCP were (73.4±16.7) points. The score of Suzhou was the lowest, while Yancheng was the highest. After 3 months of online CBL case training, the mean scores of 123 PMCP significantly improved (86.3±24.7) points, the difference was statistically significant (P < 0.001). The correct rate of core knowledge of circulatory system, skin, emergency, eye, ear, nose and throat, and rehabilitation in the post-training test was lower than that of the pre-training test, and other aspects were higher than that of the bottom test. The accuracy rate of all knowledge points of evidence-based medical thinking improved compared with the thorough test. The results of multiple linear regression analysis showed that the standardized training and online learning time of general practice residents were the main influencing factors affecting the training effect. The overall mean score of the training satisfaction survey was (67.58±12.30) points. Among them, the highest-scoring parameters were training schedule with a score of (4.38±0.84) and mastery of the new coronavirus infection diagnosis standards (4.38±0.81). The lowest-scoring parameters was the difficulty of the training questions with a score of (3.88±1.15). There were significant differences in satisfaction scores in four dimensions: training content, training organization, training effect and training method (P=0.014). Most of the research subjects believed that online training is conducive to saving training time and improving training efficiency, but the difficulty of the topic is slightly high.  Conclusion  Training based on CBL data model is conducive to improving the clinical ability of general practitioners and helping to homogenize the management of training process.

     

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