摘要
目的/意义优化患者就诊流程,缩短在院就医时间与移步路径,帮助患者预知各就诊环节时间。方法/过程基于图论与机器学习算法模型,融合医院空间布局、诊疗科室分布及患者就诊项目等数据信息,构建智能就诊路径推荐模型;基于医院大数据,构建就诊时间预测模型,预测患者在挂号、候诊、检查等各环节耗时;设计并实现智能就诊路径实时推荐系统,为患者提供清晰的就诊路径指引与较准确的耗时预估服务。结果/结论智能就诊路径实时推荐系统融合就诊时间预测与就诊路径推荐能力,提升了患者的就医体验和医院的服务效率。
Purpose/Significance To optimize the patient’s treatment process,to shorten the treatment time and moving path in the hospital,to help patients predict the time of each treatment process.Method/Process Based on graph theory and machine learning algorithm model,the intelligent treatment path recommendation model is constructed by integrating data information such as hospital spatial layout,diagnosis and treatment department distribution and patient treatment items.Based on the big data of hospital patients,the prediction model of patient treatment time is constructed to predict the time spent in registration,waiting for treatment or examination,etc.A real-time recommendation system for intelligent treatment paths is designed and implemented to provide patients with clear guidance and more accurate time-consuming estimation services.Result/Conclusion The intelligent real-time treatment path recommendation system integrates the capability of treatment time prediction and path recommendation,which significantly improves the treatment experience of patients and the service efficiency of hospitals.
作者
蒋宏建
陈健超
JIANG Hongjian;CHEN Jianchao(Wuyi Traditional Chinese Medical Hospital of Jiangmen,Jiangmen 529099,China)
出处
《医学信息学杂志》
CAS
2024年第10期90-97,共8页
Journal of Medical Informatics
关键词
就诊时间
路径推荐
就诊体验
智慧医院
treatment time
path recommendation
treatment experience
smart hospital
作者简介
蒋宏建,硕士,高级工程师,发表论文1篇;通信作者:陈健超,高级工程师。
