With the change of COVID-19, the prevention and control of COVID-19 infection epidemic entered a new stage in December 2022. How to quickly complete the emergency treatment of a large number of patients in a short period of time, and ensure that patients in emergency department can get rapid and effective medical treatment has always been an urgent problem that emergency department need to solve. The Department of Emergency Medicine of West China Hospital of Sichuan University has adopted patient-oriented management measures based on the core idea of the new public management theory, and has achieved remarkable results. Therefore, this article summarizes the workflow and nursing management strategies of the emergency department rescue area of West China Hospital of Sichuan University in dealing with the batch treatment of COVID-19 infected patients, including optimizing and correcting the environment layout of the ward, implementing the “secondary triage” mode in the rescue area, adding an inter-hospital referral platform for critical patients with COVID-19 emergency, building a conventional COVID-19 reserve material repository in the emergency department, setting up a field office for multi-department joint emergency admission service, optimizing emergency transport services for patients with COVID-19, scientific scheduling and reasonable human resource management, and providing humanistic care for employees, in order to provide reference for the management practice of the emergency department.
Objective To investigate the core competencies of emergency specialized nurses and the influencing factors in Sichuan Province so as to provide a basis for improving the training systems. Methods The trainees who received specialized training in West China Hospital every March and September between 2012 and 2014 were investigated with questionnaire survey. Results A total of 270 questionnaires were given out, and 246 valid questionnaires were retrieved. The scores of emergency specialized nurses’ core competencies ranged from 165 to 258, with an average of 214.55±22.56. According to the scores, 4.88% of the emergency specialized nurses’ core competencies were at a low level, 67.07% were at a middle level and 28.5% were at a high level. The influencing factors of core competencies included education, professional title, position, level of hospitals and years of working experience in the emergency department. Conclusion Core competencies of emergency specialized nurses need to be further improved and the training systems need to be improved consistently.
ObjectiveTo investigate nurses' attitude on the reporting of clinical adverse events and analyze its correlated factors in the Emergency Department. MethodsA total of 130 nurses in a class-3 grade-A hospital were recruited in our study by convenience sampling method during November and December 2014. The Chinese version of Reporting of Clinical Adverse Events Scale was applied to assess nurses' attitude on reporting adverse events. ResultsThe nurses' willingness to report adverse events in the Emergency Department was generally low, and the attitude scores of nurses in the triage zone, rescue zone, monitoring zone and observation zone were respectively 65.62±1.16, 65.49±0.58, 65.06±0.80, and 63.20±0.86, without any significant difference among these zones (P>0.05). The attitude scores of nurses with a seniority of 1-2, 3-5, 6-9, and ≥ 10 years were respectively 67.37±3.27, 64.49±3.98, 63.77±4.82, and 64.30±4.52, with significant differences among these seniority groups (P＜0.05). The attitude scores of nurses with a rank of nurse-in-charge, primary nurse, and nurse were respectively 61.25±4.02, 63.97±4.52, and 65.92±4.02, also with significant differences among these groups (P＜0.05). ConclusionsThe willingness of reporting clinical adverse events in emergency nurses is not high. It is necessary to strengthen the training of nurses on their cognition of adverse events and encourage reporting, thus to create a non-punishment hospital security culture.
Objective To analyze the complaint characteristics of emergency department of women and children’s specialized hospital, and to provide a basis for improving medical service quality, enhancing hospital management, increasing satisfaction, and reducing complaint rates in specialized hospitals. Methods Using the Healthcare Complaint Analysis Tool classification framework, a retrospective analysis was conducted on complaints from the Emergency Department of West China Second University Hospital of Sichuan University. Results The total number of complaints from 2020 to 2022 was 525, and the number of complaints had been increasing year by year. There were 196 complaints against personnel and 329 complaints against regions. There were 320 complaints related to management issues (61.0%), 143 complaints related to doctor-patient relationship issues (27.2%), and 62 complaints related to clinical issues (11.8%). The complained areas were mainly fever clinics (193 cases), and the complained personnel were mainly nurses (82 cases). Conclusion The emergency department of women and children’s specialized hospitals is different from comprehensive hospitals, and active optimization should be carried out to address the main issues. While continuously improving the level of medical technology, it is also necessary to strengthen information technology construction, optimize medical procedures, improve environmental facilities, and provide psychological support for patients and their caregivers.
Objective To establish and verify the early prediction model of critical illness patients with influenza. Methods Critical illness patients with influenza who diagnosed with influenza in the emergency departments from West China Hospital of Sichuan University, Shangjin Hospital of West China Hospital of Sichuan University, and Panzhihua Central Hospital between January 1, 2017 and June 30, 2020 were selected. According to K-fold cross validation method, 70% of patients were randomly assigned to the model group, and 30% of patients were assigned to the model verification group. The patients in the model group and the model verification group were divided into the critical illness group and the non-critical illness group, respectively. Based on the modified National Early Warning Score (MEWS) and the Simplified British Thoracic Society Score (confusion, uremia, respiratory, BP, age 65 years, CRB-65 score), a critical illness influenza early prediction model was constructed and its accuracy was evaluated. Results A total of 612 patients were included. Among them, there were 427 cases in the model group and 185 cases in the model verification group. In the model group, there were 304 cases of non-critical illness and 123 cases of critical illness. In the model verification group, there were 152 cases of non-critical illness and 33 cases of critical illness. The results of binary logistic regression analysis showed that age, hypertension, the number of days between the onset of symptoms and presentation at the emergency department, consciousness state, white blood cell count, and lymphocyte count, oxygen saturation of blood were the independent risk factors for critical illness influenza. Based on these 7 risk factors, an early prediction model for critical illness influenza was established. The correct percentages of the model for non-critical illness and critical illness patients were 95.4% and 77.2%, respectively, with an overall correct prediction percentage of 90.2%. The results of the receiver operator characteristic curve showed that the sensitivity and specificity of the early prediction model for critical illness influenza in predicting critical illness patients were 0.909, 0.921, and the area under the curve and its 95% confidence interval were 0.931 (0.860, 0.999). The sensitivity, specificity, and area under the curve (0.935, 0.865, 0.942) of the early prediction model for critical illness influenza were higher than those of MEWS (0.642, 0.595, 0.536) and CRB-65 (0.628, 0.862, 0.703). Conclusions The conclusion is that age, hypertension, the number of days between the onset of symptoms and presentation at the emergency department, consciousness, oxygen saturation, white blood cell count, and absolute lymphocyte count are independent risk factors for predicting severe influenza cases. The early prediction model for critical illness patients with influenza has high accuracy in predicting severe influenza cases, and its predictive value and accuracy are superior to those of the MEWS score and CRB-65 score.
Objective To analyze the characteristics of patients transferred by ambulances to emergency department before and after coronavirus disease 2019 epidemic, in order to improve the efficiency of emergency triage, optimize the utilization of emergency resources, and provide a reference for standardized tiered medical services in different situation. Methods The patients’ information collected through Wenjuanxing questionnaire was extracted, who were transferred by ambulances to the Emergency Department of West China Hospital of Sichuan University between December 27th, 2018 and April 28th, 2019 (before epidemic), or between December 27th, 2019 and April 28th, 2020 (during epidemic), or between December 27th, 2020 and April 28th, 2021 [in regular epidemic prevention and control period (REPCP)]. The general information, sources, reasons for referral, disease spectrum and triage levels of patients in the three periods were compared. Results There were 3993, 2252 and 1851 cases before epidemic, during epidemic, and in REPCP, respectively. The differences in gender and age among the three periods were not statistically significant (P>0.05). The percentage of referrals from tertiary hospitals in each period was 74.00%, 72.65%, and 76.12%, respectively, which was higher in REPCP than that during epidemic (P<0.05). The percentage of direct referrals from emergency department in each period was 41.00%, 42.14%, and 44.46%, respectively, which was higher in REPCP than that before epidemic (P<0.05). The percentage of two-way referrals in each period was 37.79%, 36.63%, and 34.36%, respectively, which was lower in REPCP than that before epidemic (P<0.05). During epidemic and in REPCP, the proportions of referrals due to “need for surgery” (24.72%, 27.84%, and 28.74%, respectively) and “request by family members” (49.64%, 53.33%, and 56.24%, respectively) increased compared with those before epidemic (P<0.05), while the proportion of referrals due to “critical illness” decreased compared with that before epidemic (40.20%, 35.21%, and 33.17%, respectively; P<0.05); the proportion of referrals due to “diagnosis unknown” decreased in REPCP compared with that before epidemic (15.50%, 13.90%, and 11.89%, respectively; P<0.05). The proportion of acute aortic syndromes in REPCP increased compared with that during epidemic (3.46%, 2.98%, and 4.65%, respectively; P<0.05), the proportion of trauma in REPCP increased compared with that before epidemic (13.72%, 15.76%, and 17.77%, respectively; P<0.05), and the proportion of pneumonia/acute exacerbation of chronic obstructive pulmonary disease during epidemic and in REPCP decreased compared with that before epidemic (8.44%, 3.73%, and 3.84%, respectively; P<0.05). The proportion of critically ill patients referred in each period was 72.88%, 75.58%, and 79.15%, respectively, which was the highest in REPCP (P<0.05). Conclusions The epidemic has a significant impact on emergency ambulance referrals, and emergency triage needs to be continuously optimised and improved in staff, facilities, processes and management. It is necessary to further improve the implementation of hierarchical diagnosis and treatment, strengthen information communication between referral and emergency departments of receiving hospitals, and improve referral efficiency.