麻醉手术后随访指标体系与结构化随访系统的构建  

Construction of a follow‑up indicator system and a structured information system after anesthesia for surgery

作　　者：朱易豪 朱涛[1,2,3] 郝学超 Zhu Yihao;Zhu Tao;Hao Xuechao(Department of Anesthesia and Operating Center,West China Hospital,Sichuan University,Chengdu 610041,China;National Clinical Research Center for Geriatrics,West China Hospital,Sichuan University,Chengdu 610041,China;Research Unit for Perioperative Stress Assessment and Clinical Decision,Chinese Academy of Medical Sciencesb(2018RU012),West China Hospital,Sichuan University,Cheng-du 610041,China;Department of Anesthesiology,Sichuan Cancer Hospital&Institute,Chengdu 610041,China)

机构地区：[1]四川大学华西医院麻醉手术中心,成都610041 [2]国家老年疾病临床医学研究中心,成都610041 [3]中国医学科学院围术期应激风险评估与临床决策创新单元(2018RU012),成都610041 [4]四川省肿瘤医院·研究所麻醉科,成都610041

出　　处：《国际麻醉学与复苏杂志》2023年第1期42-47,共6页International Journal of Anesthesiology and Resuscitation

基　　金：“十三五”国家重点研发计划项目(2018YFC2001800);国家老年疾病临床医学研究中心项目(Z2018A02);四川大学华西医院1·3·5项目(ZYJC18010);中国医学科学院医学与健康科技创新工程项目(2019‑I2M‑5‑011);四川省科技厅重点研发项目(2019YFG0491)。

摘　　要：目的构建麻醉手术不同时间点随访指标体系,研发建立结构化的随访信息系统,以满足麻醉医疗质控和科研需求。方法通过查阅文献和咨询专家构建完备的随访指标体系,向全国多家医院麻醉科医师发送电子问卷,对构建的随访指标体系进行信度分析及效度分析,并形成推荐的术后7 d、术后30 d、术后1年随访指标体系;运用互联网、标注化语义定义、人工智能等技术,构建结构化的随访信息系统。结果2021年6月1日至2021年6月30日,通过问卷星发放随访指标集调查问卷,共回收来自24个省94家医院的有效匿名回复问卷185份,随访体系肯德尔和谐系数为0.525~0.566,条目水平内容效度指数为0.30~0.98。推荐的术后7 d随访体系包含8个系统30个条目;术后30 d随访体系包含2个系统,共计2个条目;术后1年随访体系无推荐条目。成功研发建立基于上述随访指标体系的结构化、智能化随访信息系统。目前,可通过院内电脑或移动设备访问该随访系统,已完成临床试用并常规用于随访。试运行期间结果表明,随访人员对该系统满意度较高,随访平均准确率提高了16%,随访时间降低10~15 min/例。结论依据与麻醉相关性的不同,在麻醉手术后不同时间需重点关注的结局指标存在差异,结构化随访信息系统可提高随访效率及准确率,为相关研究提供新的工具和方法,增加不同临床研究的可比性。Objective To establish a follow‑up indicator system at different time points after anesthesia for surgery and de‑velop a structured follow‑up information system to meet the needs for quality control and scientific research in anesthesiology.Methods Through literature review and expert consultation,a complete follow‑up indicator system was constructed.Then,an elec‑tric questionnaire was sent to anesthesiologists in hospitals across the country.The established follow‑up indicator system was evaluat‑ed through reliability analysis and validity analysis and a recommended follow‑up indicator system at postoperative 7 days,30 days and 1 year was constructed.Through internet technology,marking semantic definition,and artificial intelligence technology,a struc‑tured follow‑up information system was established.Results From June 1 to 30,2021,the questionnaire was distributed through the internet,and a total of 185 effective anonymous responses were collected from 94 hospitals in 24 provinces,with the Kendall coefficient of 0.525‒0.566 and the item‑level content validity index of 0.30‒0.98,respectively.The recommended follow‑up indicator system at postoperative 7 days included 30 items in 8 systems.The follow‑up indicator system at postoperative 30 days included 2 items in 2 systems.The follow‑up indicator system at postoperative 1 year did not have any recommended item.Based on the above follow‑up indica‑tor system,a structured and intelligent follow‑up information system was successfully developed.The follow‑up system was able to be accessed through hospital computers or mobile devices,and have been routinely applied in follow‑up visits after clinical trials.The re‑sults of the trial run showed that the follow‑up system had high satisfaction from those followed‑up,with 16%increase in average follow‑up accuracy,and 10‒15 min decrease in follow‑up time per case.Conclusions In light of their correlation with anesthesia,the overcome indicators that should be paid attentio

关 键 词：麻醉 随访 指标体系 信息系统 

分 类 号：R614[医药卫生—麻醉学]