基于人工智能的患者门诊服务评价与改进实践  

Evaluation and Improvement Practice of Outpatient Service Based on Artificial Intelligence

作　　者：章静[1] 黄磊[1] 段美芹[1] ZHANG Jing;HUANG Lei;DUAN Mei-qin(Hangzhou Hospital of Traditional Chinese Medicine)

机构地区：[1]杭州市中医院

出　　处：《医院管理论坛》2022年第3期43-45,25,共4页Hospital Management Forum

基　　金：浙江省中医药科技计划项目,编号:2019ZA080。

摘　　要：目的 基于患者在线评价及现场调查结果分析医院门诊服务存在的缺陷,进行优化改进,评估方法及改进效果。方法 收集门诊短信在线评论中的差评文本,对差评内容进行分类统计;另由第三方调查公司在门诊现场随机调查480名就诊患者,对问卷结果作分类统计,根据上述统计结果制定门诊服务优化管理方案,以改进门诊服务缺陷。结果 线上收集到227条患者在线差评有效文本,线下459份有效问卷中差评29份,所有差评文本经文本处理、情感分析、差评倾向量化,得到差评倾向最严重的分别是尊重、制度流程与沟通,作为门诊服务优化改进重点。结论 患者在线评价及现场调查分析可有效发现门诊服务缺陷,为门诊服务质量改进优化提供数据支持。Objective To analyze the defects of hospital outpatient service based on patient online comments and on-site responses and to evaluate the effect of improvement measures.Methods The bad review texts of outpatient service were collected and classified.On-site survey was conducted randomly in 480 patients seeking outpatient service by a third party investigation company.The results of the survey were analyzed.Optimization plan of outpatient service was developed based on the findings to address the defects of outpatient service.Results A total of 227 valid online bad review texts of were collected,and 29 of 459 valid offline questionnaires were bad reviews.Through text processing,sentiment analysis and bad review tendency quantification of the bad reviews,it was found that the bad reviews were more likely about respect,system flow and communication,which should be the focus of outpatient service optimization.Conclusion Online comments and onsite survey can effectively reveal the defects of outpatient service and provide data support for the improvement of outpatient service quality.

关 键 词：门诊 服务质量 在线评论 现场调查 服务缺陷 

分 类 号：R197.3[医药卫生—卫生事业管理]