基于大数据模型ChatGLM的医院交通管理对策研究  

Research on Hospital Traffic Management Countermeasures Based on ChatGLM

作　　者：王鑫 WANG Xin(Tianjin Chest Hospital)

机构地区：[1]天津市胸科医院

出　　处：《医院管理论坛》2025年第1期33-35,32,共4页Hospital Management Forum

摘　　要：目的分析医院停车现状及存在的问题,借助ChatGLM数据模型提出针对性的解决策略,以改善医院停车状况及周边交通环境。方法运用ChatGLM大数据模型,对驾车就诊人员的就诊时间进行精准预测。在此基础上,构建停车排队管理系统,以有效降低医院停车场的排队等候时间,提升医院周边道路的通行效率。结果实施基于患者就诊时间预测的医院交通管理系统后,医院周边交通拥堵状况得到了有效缓解。患者因交通拥堵而额外增加的就诊时间大幅减少,特别是在疾病高发期,提升了患者的就医体验。结论基于大数据模型ChatGLM的医院交通管理系统有效改善了医院周边入院交通拥堵情况,减少了患者因入院交通拥堵而增加的就诊时间。通过细化预测数据、优化模型参数、构建信息化通知平台等措施,可以进一步提升系统的性能和预测准确性,为患者提供更加便捷、高效的医疗服务。Objective To analyze the current situation and existing problems of hospital parking,and propose specific solutions with ChatGLM data model to improve the parking situation and surrounding traffic environment.Methods ChatGLM big data model was used to accurately predict the time of appointment for patients coming by cars.On this basis,the parking queue management system was constructed to effectively reduce the queuing time of the hospital parking lot and improve the traffic efficiency of the roads around the hospital.Results After the implementation of the hospital traffic management system based on the prediction of patients’time of appointment,the traffic congestion around the hospital was effectively alleviated.Additional time for patients due to traffic congestion were significantly reduced,especially during periods of high disease incidence,which enhanced the patient's medical experience.Conclusion The hospital traffic management system based on ChatGLM big data model can effectively improve the traffic congestion around the hospital,and reduce the patients'additional time to see a doctor due to the traffic congestion.By refining forecast data,optimizing model parameters,and building an information notification platform,the performance and prediction accuracy of the system can be further improved,and more convenient and efficient medical services can be provided to patients.

关 键 词：就诊时间 大数据模型 交通管理 

分 类 号：R197.5[医药卫生—卫生事业管理]