智能化语言云预检分诊系统对急诊胸痛中心就诊患者急诊分诊准确率及家属护理工作满意度的影响

Influence of Intelligent Language Cloud Pre-Examination and Triage System on the Accuracy of Emergency Triage of Patients in Emergency Chest Pain Center and the Satisfaction of Family Members’ Nursing Work

目的 探讨智能化语言云预检分诊系统对急诊胸痛中心就诊患者急诊分诊准确率及家属护理工作满意度的影响。方法 回顾性选取2018年6月至2020年12月驻马店市中心医院急诊胸痛中心就诊患者256例,根据治疗方法不同分组,采用常规分诊模式的纳入对照组(N=121),采用智能化语言云预检分诊系统的纳入研究组(N=135)。比较2组急诊分诊准确率、候诊时间、各时间节点情况、诊间意外发生情况、主要不良事件发生情况(包括心力衰竭、恶性心律失常、昏迷、心源性休克)及家属护理工作满意度。结果 研究组急诊分诊准确率高于对照组,诊间意外发生率低于对照组;时间节点中首份心电图时间、肌钙蛋白出结果时间、DTOB时间(门球时间door to balloon time)、候诊时间均较短于对照组;主要不良事件发生率低于对照组,而家属护理工作满意对照组高于对照组;医护人员就诊优先性、分诊准确性、候诊有序性、使用方便性及患者依从性评分高于对照组,差异均有统计学意义(P<0.05)。结论 急诊胸痛中心就诊患者应用智能化语言云预检分诊系统,能显著缩短就诊时间,降低诊间意外发生率,提高急诊分诊准确率,降低主要不良事件发生风险,增强家属护理工作满意度及医护人员满意度。

Objective To explore the impact of intelligent language cloud pre-examination and triage system on the accuracy of emergency triage and the satisfaction of family members’ nursing work of patients in emergency chest pain center. Methods A total of 256 patients who visited the Emergency Chest Pain Center of Zhumadian Central Hospital from June 2018 to December 2020 were retrospectively selected and grouped according to the different treatment methods, those who adopted the conventional triage mode were included in the control group(N=121), and those who adopted the intelligent language cloud pre examination triage system were included in the study group(N=135). The accuracy of emergency triage, waiting time, situation of each time node, occurrence of accidents during consultations, occurrence of major adverse events(including heart failure, malignant arrhythmia, coma, cardiogenic shock) and family nursing satisfaction were compared between the two groups. Results The accuracy rate of emergency triage in the study group was higher than that in the control group, and the incidence of accidents during diagnosis was lower than that in the control group, the time of the first ECG, the time of troponin results, the time of DTOB(door to balloon time), and the waiting time in the study group were shorter than those in the control group;The incidence of major adverse events in the study group was lower than that in the control group, while the satisfaction of family members’ nursing work in the study group was higher that in the control group, the medical staff in the study group had higher priority of seeing a doctor, accuracy of triage, order of waiting, ease of use and patient compliance scores than in the control group, with significant differences(All P<0.05). Conclusion The application of intelligent language cloud pre-examination and triage system for patients in emergency chest pain center can significantly shorten the treatment time, reduce the incidence of accidents during consultations, improve the accuracy of emergency triage, reduce the occurrence risk of major adverse events, and enhance the nursing work satisfaction degree of family members and medical staff satisfaction degree.