智能早期预警评分系统对非重症患者预后评估的价值研究  

Effect of intelligent early warning scoring system in condition monitoring of hospitalized non-critically ill patients

作　　者：黄冰瑛 唐佳迎 宋剑平[1] 张玉萍[1] 赵飞 王莺 洪灵玲[2] 兰美娟[1] Huang Bingying;Tang Jiaying;Song Jianping;Zhang Yuping;Zhao Fei;Wang Ying;Hong Lingling;Lan Meijuan(Nursing Depariment,the Second Affiliated Hospital,Zhejiang University School of Medicine,Hangzhou 310000 China;Information Techrology Center,the Second Affiliated Hospital,Zhejiang University School of Medicine,Hangzhou 310000,China)

机构地区：[1]浙江大学医学院附属第二医院护理部,杭州310000 [2]浙江大学医学院附属第二医院IT中心,杭州310000

出　　处：《中华急诊医学杂志》2022年第9期1243-1248,共6页Chinese Journal of Emergency Medicine

摘　　要：目的建立并应用智能早期预警评分系统(electronic further modified early warning score system,e-fMEWS),探讨其在非重症单元住院患者病情评估及预警中的作用,以期为临床护理人员提供早期、动态识别患者病情潜在恶化风险的方法。方法回顾性分析2018年1月至12月及2020年1月至12月浙江大学医学院附属第二医院多个非重症单元住院患者262805例。其中2018年1月至12月住院的患者作为对照组,由责任护士使用传统的单一评估指标启动应急反应系统;2020年1月至12月的患者作为研究组,应用e-fMEWS启动应急反应系统。研究对象的纳入标准:(1)患者住院时间≥24h;(2)患者年龄≥14周岁。排除标准:(1)患者入院前进行过心肺复苏;(2)患者治疗中途中止治疗或者转院;(3)接受姑息治疗患者;(4)急诊预检分诊I级收治非重症病区的患者。比较两组患者快速反应小组(rapid response team,RRT)启动情况、心搏呼吸骤停小组启动情况,以及启动RRT的患者心搏呼吸骤停发生例数、有创机械通气例数、转入重症监护室例数、住院天数及预后情况。采用统计学软件SPSS 22.0进行数据的处理与分析。结果e-fMEWS评估下,与对照组相比,研究组心搏呼吸骤停小组启动比例下降0.03%;启动RRT的患者平均住院天数缩短,发生院内呼吸心搏骤停例数下降(12.2%vs.13.2%)及转入重症监护单元例数较少(42.8%vs.50.6%),治愈/好转率提高(58.4%vs.56.1%)。结论应用e-fMEWS有助于临床护理人员快速、准确识别患者病情潜在恶化风险,通过早期识别非重症单元的潜在重症患者,早期干预、及时治疗,避免不良事件发生,改善患者预后。Objective To establish and apply the electronic further modified early warning score system(e-fMEWS),and explore its role in the condition evaluation and early warning of inpatients in noncritical units,so as to provide clinical nurses with an early and dynamic method to identify the potential deterioration risk of patients'condition.MethodsA retrospective analysis of 262805 inpatients in multiple non-critical units of the Second Affliated Hospital of Zhejiang University School of Medicine from January to December 2018 and January to December 2020 was performed.The patients who were hospitalized from January to December 2018 were used as the control group,and the responsible nurse used the traditional single evaluation index to start the emergeney response system;the patients from January to December 2020 were used as the research group,and the emergency response system was started using e-fME WS.The inclusion criteria were as folows:(1)hospialization time≥24 h;(2)patient≥14 years old.Exclusion criteria were as follows:(1)patients had cardiopulmonary resuscitation before admission;(2)patients discontinued treatment or were transferred to another hospital during treatment;(3)patients received palliative care;(4)patients were admitted to non-critical wards in grade I of emergeney pre-examination and triage.The activation of the rapid response leam(RRT),the activation of the cardiorespiratory arrest team,the incidence of cardiac and respiratory arrest,the number of cases of invasive mechanical ventilation,the number of cases admitted to the intensive care unit,the length of hospital stay and the prognosis were compared.,Statistical sofiware SPss 22.0 was used for data analysis.Results Under the e-fMEWS assessment,compared with thc control group,the rate of initiation of the research group decreased by 0.03%.For patients who initiated RRT,the average length of hospital staywas shortened,and the number of in-hospital respiratory cardiac arrest deereased(12.2%vs.13.2%)and the number of cases trans ferred to the int

关 键 词：智能早期预警评分 人工智能 快速反应团队 护理 

分 类 号：R473[医药卫生—护理学]