摘要
目的 鉴于医疗技术的进步对临床规培护士操作能力的重要性，本研究旨在通过需求预测模型和数据驱动的教学方法，提升临床规培护士的操作能力，从而提高医疗服务质量和病人满意度。方法 我们收集了临床规培护士的操作能力培训数据，构建了一个需求预测模型，并根据模型预测结果，设计并实施了一套数据驱动的教学策略。结果 研究结果表明，相比传统教学方法，我们的需求预测模型和数据驱动教学方法能更有效地提升临床规培护士的操作能力，特别是在药物管理、疾病预防和控制以及紧急情况处理等复杂操作中。此外，这种方法还帮助临床教师更深入地理解并满足学生的学习需求，从而优化教学效果。结论 本研究结果揭示，需求预测模型和数据驱动的教学方法在提升临床规培护士操作能力方面具有显著的应用价值。这不仅能有效提升护士的操作能力，同时也能助力教师更深入地理解并满足学生的学习需求，从而优化教学效果。
关键词： 需求预测模型；临床规培护士；操作能力；数据驱动的教学方法
Abstract
Objective Given the importance of the operational capability of clinical training nurses in the context of medical technology advancements, this study aims to enhance the operational capability of clinical training nurses and thereby improve the quality of medical services and patient satisfaction through the use of demand forecasting models and data-driven teaching methods. Methods We collected operational capability training data from clinical training nurses, constructed a demand forecasting model, and designed and implemented a set of data-driven teaching strategies based on the model’s predictions. Results The results of the study indicate that, compared to traditional teaching methods, our demand forecasting model and data-driven teaching methods can more effectively enhance the operational capability of clinical training nurses, especially in complex operations such as drug management, disease prevention and control, and emergency situation handling. Furthermore, this method also helps clinical teachers to better understand and meet the learning needs of students, thereby optimizing teaching outcomes. Conclusion The results of this study reveal that the demand forecasting model and data-driven teaching methods have significant application value in enhancing the operational capability of clinical training nurses. This not only effectively enhances the operational capability of nurses, but also helps teachers to better understand and meet the learning needs of students, thereby optimizing teaching outcomes.
Key words： Demand Forecasting Model; Clinical Training Nurses; Operational Capability; Data-Driven Teaching Methods
参考文献 References
[1] 王婷,周蓉,马玉红,等.信息化平台在护士规范化培训中的应用研究 I.护理学报
[2] A. Rajkomar, J. Dean, and I. Kohane, “Machine learning in medicine,” New England Journal of Medicine, vol. 380, no. 14, pp. 1347-1358, 2019.
[3] J. H. Chen and S. M. Asch, “Machine learning and prediction in medicine—beyond the peak of inflated expectations,” New England Journal of Medicine, vol. 376, no. 26, pp. 2507-2509, 2017.
[4] A. Esteva et al., “A guide to deep learning in healthcare,” Nature medicine, vol. 25, no. 1, pp. 24-29, 2019.
[5] Z. Obermeyer and E. J. Emanuel, “Predicting the future—big data, machine learning, and clinical medicine,” New England Journal of Medicine, vol. 375, no. 13, pp. 1216, 2016.
[6] R. C. Deo, “Machine learning in medicine,” Circulation, vol. 132, no. 20, pp. 1920-1930, 2015.
[7] D. Ravi et al., “Deep learning for health informatics,” IEEE journal of biomedical and health informatics, vol. 21, no. 1, pp. 4-21, 2017.
[8] 邓英，宫玉翠,许红红,等，从预防压疮宣教知识需求的视觉研究专科护多学科团队的作用 .国际护理学杂志.2020.39(3):394-397.