中国急诊医学影像现状调查分析

A survey report on the status of emergency radiology in China

目的调研中国急诊医学影像现状,为急诊医学影像的规范发展、科学管理和大数据研究提供数据支持。方法本研究由中国急诊医学影像数据库协作组发起,于2022年8月12日至10月19日,通过问卷调查的方式全面调查国内以数字化X线摄影术(DR)和CT为主的急诊医学影像现状的相关数据,包括急诊影像人员、设备、工作量、危急值报告流程、人工智能(AI)应用现状5个方面。结果全国共123家医院参与完成了调查。调查显示69.1%的急诊DR/CT报告由住院医师及以上人员完成。应用于急诊患者影像检查的DR品牌有21家,CT品牌有10家,MR品牌有8家。调研的三级医院及二级医院2022年1月至6月DR检查量中位数分别为4642、2015例,CT检查量中位数分别为16512、3762例。三级医院急诊白班、夜班DR平均单班次工作量主要为≤20、21~50份,急诊白班、夜班CT平均单班次工作量主要为21~50、51~100份,而二级医院急诊白班/夜班DR/CT平均单班次工作量均主要为≤20份。危急值报告流程方面,74.8%的急诊影像医师和84.6%的急诊影像技师采取电话/短信通知临床医师或患者家属。AI在急诊影像的整体部署率为60.2%。有75%的受访者认为未来AI能够从急诊筛查、辅助诊断和流程优化等方面改善急诊影像工作。结论DR和CT为主的急诊影像存在报告医师年资普遍偏低,影像设备品牌丰富多样,检查量及医师人均工作量大,尤以三级医院为著,危急值报告流程仍主要依赖传统手段等现状。目前AI在急诊影像领域初露头角,未来发挥AI在急诊影像智能全流程方面的巨大潜能仍任重道远。

Objective To investigate the application status of emergency radiology in China,and to provide data support for the standardized development,scientific management and big data research of emergency radiology.Methods From August 12th to October 19th,2022,a questionnaire survey was conducted through WeChat"Questionnaire Star"to send targeted questionnaires to investigate the relevant data of the current status of emergency radiology in China,mainly including digital radiography(DR)and computed tomography(CT).This study was initiated by the Chinese Emergency Radiology Database Collaboration Group,and comprehensively investigated emergency imaging personnel,equipment,workload,critical value reporting process,and artificial intelligence(AI)application status.Results There were 123 hospitals in the study.The survey showed that emergency DR/CT reports were mainly completed by residents and above(69.1%).There were 21 DR brands,10 CT brands and 8 MR brands used for emergency imaging examinations.The median number of DR examinations in tertiary hospitals and secondary hospitals investigated from January to June 2022 was 4642 and 2015 cases respectively,and the median number of CT examinations was 16512 and 3762 cases respectively.The average single-shift workload of DR in the emergency radiology department during the day and night shift in tertiary hospitals was mainly≤20 copies and 21-50 copies,and the average single-shift workload of CT in the emergency radiology department during the day and night shift was mainly 21-50 copies and 51-100 copies,while the average single-shift workload of DR/CT in the emergency radiology department during the day/night shift in secondary hospitals was mainly≤20 copies.In terms of critical value reporting process,74.8%of emergency imaging doctors and 84.6%of emergency imaging technicians took the way of phone/text message to notify the clinical doctor or the patients′family.The overall deployment rate of AI in emergency imaging was about 60.2%.75%of the respondents believed that in the future,AI can improve emergency radiology work from aspects such as emergency screening,aided diagnosis and process optimization.Conclusions The emergency medical imaging mainly based on DR and CT has the current situations such as generally low seniority of doctors,diverse brands of imaging equipments,large volume of examinations and intense workload per doctor,especially in tertiary hospitals,and dependence on traditional means for critical value reporting.At present,AI is emerging in the field of emergency imaging,and there is still a long way to go to play the huge potential of AI in the intelligent whole process of emergency imaging in the future.