<span style="font-family:Verdana;">Purpose: </span><span style="font-family:Verdana;">To discuss the effect of “1 + 3 + 3” emergency management mode to deal with COVID-19 pandem...<span style="font-family:Verdana;">Purpose: </span><span style="font-family:Verdana;">To discuss the effect of “1 + 3 + 3” emergency management mode to deal with COVID-19 pandemic in fever outpatient service of general hospitals. Method: This paper analyzes and summarizes the problems encountered by fever outpatient service in dealing with the COVID-19 pandemic from three aspects of “One Team”, “Three-Key” Control and “Three Mosts”. Results: The application of “1 + 3 + 3” emergency management mode can effectively boost the orderliness and efficiency of fever outpatient service in dealing with COVID-19 pandemic. Conclusion: The “1 + 3 + 3” emergency management mode provides a new management mode and idea for dealing with COVID-19 pandemic,</span><span style="font-family:""> </span><span style="font-family:Verdana;">so the fever outpatient service of general hospitals can better improve the national overall anti-pandemic situation.展开更多
This study investigates the construction of a health management service mode based on large-scale comprehensive hospitals by analyzing health management service modes at home and abroad,that is,taking the Affiliated H...This study investigates the construction of a health management service mode based on large-scale comprehensive hospitals by analyzing health management service modes at home and abroad,that is,taking the Affiliated Hospital of Chifeng University as an example,establish a health examination hospital,undertake core tasks such as health service operation process,system,monitoring,and system formulation,and take the best medical resources.Attract social medical resources to collaborate and give health service mode of health status monitoring,evaluation,and intervention to health service objects,aided by advanced medical technology.To extend the traditional health management service with the hospital as the protagonist to health management with participation from family and society beyond the hospital,forming a closed-loop,rapid,and efficient health service management system.Thus,through graded quality services,to lessen the difficulties of patients seeing a doctor and to solve the problem of overcrowding and minor ailments in major hospitals.展开更多
Background： Since the 1980s, severity of illness scoring systems has gained increasing popularity in Intensive Care Units （ICUs）. Physicians used them for predicting mortality and assessing illness severity in clin...Background： Since the 1980s, severity of illness scoring systems has gained increasing popularity in Intensive Care Units （ICUs）. Physicians used them for predicting mortality and assessing illness severity in clinical trials. The objective of this study was to assess the performance of Simplified Acute Physiology Score 3 （SAPS 3） and its customized equation for Australasia （Australasia SAPS 3, SAPS 3 [AUS]） in predicting clinical prognosis and hospital mortality in emergency ICU （EICU）. Methods： A retrospective analysis of the EICU including 463 patients was conducted between January 2013 and December 2015 in the EICU of Peking University Third Hospital. The worst physiological data of enrolled patients were collected within 24 h after admission to calculate SAPS 3 score and predicted mortality by regression equation. Discrimination between survivals and deaths was assessed by the area under the receiver operator characteristic curve （AUC）. Calibration was evaluated by Hosmer-Lemeshow goodness-of fit test through calculating the ratio of observed-to-expected numbers of deaths which is known as the standardized mortality ratio （SMR）. Results： A total of 463 patients were enrolled in the study, and the observed hospital mortality was 26.1% （121/463）. The patients enrolled were divided into survivors and nonsurvivors. Age, SAPS 3 score, Acute Physiology and Chronic Health Evaluation Score 11 （APACHE 11）, and predicted mortality were significantly higher in nonsurvivors than survivors （P 〈 0.05 or P 〈 0.01 ）. The AUC （95% confidence intervals [C/s]） for SAPS 3 score was 0.836 （0.796-0.876）. The maximum of Youden＇s index, cutoff, sensitivity, and specificity of SAPS 3 score were 0.526%, 70.5 points, 66.9%, and 85.7%, respectively. The Hosmer-Lemeshow goodness-of-fit test for SAPS 3 demonstrated a Chi-square test score of 10.25, P = 0.33, SMR （95% CI） = 0.63 （0.52 0.76）. The Hosmer-Lemeshow goodness-of fit test tbr SAPS 3 （AUS） demonstrated a Chi-square test score of 9.55, P 0.38, SMR （95% CI） 0.68 （0.57-0.81）. Univariate and multivariate analyses were conducted for biochemical variables that were probably correlated to prognosis. Eventually, blood urea nitrogen （BUN）, albumin,lactate and free triiodothyronine （FT3） were selected as independent risk factors for predicting prognosis. Conclusions： The SAPS 3 score system exhibited satisfactory performance even superior to APACHE 11 in discrimination. In predicting hospital mortality, SAPS 3 did not exhibit good calibration and overestimated hospital mortality, which demonstrated that SAPS 3 needs improvement in the future.展开更多
文摘<span style="font-family:Verdana;">Purpose: </span><span style="font-family:Verdana;">To discuss the effect of “1 + 3 + 3” emergency management mode to deal with COVID-19 pandemic in fever outpatient service of general hospitals. Method: This paper analyzes and summarizes the problems encountered by fever outpatient service in dealing with the COVID-19 pandemic from three aspects of “One Team”, “Three-Key” Control and “Three Mosts”. Results: The application of “1 + 3 + 3” emergency management mode can effectively boost the orderliness and efficiency of fever outpatient service in dealing with COVID-19 pandemic. Conclusion: The “1 + 3 + 3” emergency management mode provides a new management mode and idea for dealing with COVID-19 pandemic,</span><span style="font-family:""> </span><span style="font-family:Verdana;">so the fever outpatient service of general hospitals can better improve the national overall anti-pandemic situation.
基金The 2021 Chifeng natural science research project“Research on Optimization of health management mode of Chifeng Class 3A general public hospital”(Project number:2021-40)。
文摘This study investigates the construction of a health management service mode based on large-scale comprehensive hospitals by analyzing health management service modes at home and abroad,that is,taking the Affiliated Hospital of Chifeng University as an example,establish a health examination hospital,undertake core tasks such as health service operation process,system,monitoring,and system formulation,and take the best medical resources.Attract social medical resources to collaborate and give health service mode of health status monitoring,evaluation,and intervention to health service objects,aided by advanced medical technology.To extend the traditional health management service with the hospital as the protagonist to health management with participation from family and society beyond the hospital,forming a closed-loop,rapid,and efficient health service management system.Thus,through graded quality services,to lessen the difficulties of patients seeing a doctor and to solve the problem of overcrowding and minor ailments in major hospitals.
文摘Background： Since the 1980s, severity of illness scoring systems has gained increasing popularity in Intensive Care Units （ICUs）. Physicians used them for predicting mortality and assessing illness severity in clinical trials. The objective of this study was to assess the performance of Simplified Acute Physiology Score 3 （SAPS 3） and its customized equation for Australasia （Australasia SAPS 3, SAPS 3 [AUS]） in predicting clinical prognosis and hospital mortality in emergency ICU （EICU）. Methods： A retrospective analysis of the EICU including 463 patients was conducted between January 2013 and December 2015 in the EICU of Peking University Third Hospital. The worst physiological data of enrolled patients were collected within 24 h after admission to calculate SAPS 3 score and predicted mortality by regression equation. Discrimination between survivals and deaths was assessed by the area under the receiver operator characteristic curve （AUC）. Calibration was evaluated by Hosmer-Lemeshow goodness-of fit test through calculating the ratio of observed-to-expected numbers of deaths which is known as the standardized mortality ratio （SMR）. Results： A total of 463 patients were enrolled in the study, and the observed hospital mortality was 26.1% （121/463）. The patients enrolled were divided into survivors and nonsurvivors. Age, SAPS 3 score, Acute Physiology and Chronic Health Evaluation Score 11 （APACHE 11）, and predicted mortality were significantly higher in nonsurvivors than survivors （P 〈 0.05 or P 〈 0.01 ）. The AUC （95% confidence intervals [C/s]） for SAPS 3 score was 0.836 （0.796-0.876）. The maximum of Youden＇s index, cutoff, sensitivity, and specificity of SAPS 3 score were 0.526%, 70.5 points, 66.9%, and 85.7%, respectively. The Hosmer-Lemeshow goodness-of-fit test for SAPS 3 demonstrated a Chi-square test score of 10.25, P = 0.33, SMR （95% CI） = 0.63 （0.52 0.76）. The Hosmer-Lemeshow goodness-of fit test tbr SAPS 3 （AUS） demonstrated a Chi-square test score of 9.55, P 0.38, SMR （95% CI） 0.68 （0.57-0.81）. Univariate and multivariate analyses were conducted for biochemical variables that were probably correlated to prognosis. Eventually, blood urea nitrogen （BUN）, albumin,lactate and free triiodothyronine （FT3） were selected as independent risk factors for predicting prognosis. Conclusions： The SAPS 3 score system exhibited satisfactory performance even superior to APACHE 11 in discrimination. In predicting hospital mortality, SAPS 3 did not exhibit good calibration and overestimated hospital mortality, which demonstrated that SAPS 3 needs improvement in the future.
