Objective To discuss the validity and the feasibility of modified specific immunotherapy of hypoglossis allergen in the treatment of children allergic asthma. Methods 100 children with allergic asthma were selected from October,2007 to April ,2008 in our hospital and divided into the observation group and the control group. The control group adopted routine method, the observation group made modifi-cation based upon routine nursing, placing emphasis on intervention of cognition and behavior of children and their parents, improvement of treatment compliance, whole- process, dynamic and continuous observa-tion of the treatment process, making individualized health education plan. The treatment compliance, total score of asthma control, and pulmonary function examination of impulse oscillation(IOS) were compared be-tween the two groups. Results The observation group was superior to the control group in treatment com-pliance, pulmonary function examination and the control results of asthma. Conclusions Specific im-munotherapy of hypoglossis allergen combined with modified nursing method can increase treatment com-pliance of children and lead to better results.

Objective To investigate the epidemiological characteristics of gonorrhea,and to analyze its temporal-spatial clustering in Zhejiang province.Methods Data on the incidence and demographic characteristics of gonorrhea in Zhejiang province from January 2004 to December 2012 were obtained from the China Information System for Disease Control and Prevention.The population,time and space distributions of gonorrhea were described.Epidemic curve and incidence maps were drawn.A space-time permutation scan statistic was used to detect space-time clusters,and spatial autocorrelation analysis was performed to calculate the Moran's I value and draw Local Indicators of Spatial Association (LISA) cluster maps.Results In Zhejiang province,a total of 199 956 cases of gonorrhea were reported with a decreasing trend in incidence rate from 2004 to 2012.The male to female ratio was 3.51:1 (155 634/44 331).People aged between 25 and 60 years accounted for 75.21％ of these patients,whereas the constituent ratio of people aged 0-1 years and ＞ 60 years increased with time.The incidence rate of gonorrhea was significantly higher in middle and north parts than in the south part of Zhejiang province,and higher in summer than in winter and spring with the peak incidence observed in August.Thirteen temporal-spatial clusters were detected,with the large clusters in Hangzhou,Huzhou,Ningbo,Shaoxing and their neighbor counties/cities/ districts,as well as some counties/cities/districts in Jinhua.All of the above clusters lasted 4.5 years.LISA maps showed an increasing trend in high-high aggregation counties/cities/districts which spread from the north to south part of Zhejiang province.Conclusion There is a temporal-spatial aggregation of gonorrhea in Zhejiang province with young and middle-aged men as the main affected population.

Objective To learn the recent development and regional distribution of clinics in China.Methods Based on statistics and a nationwide survey of clinics in the country,a simple linear regression was made to find factors determining clinics regional distribution.Results Clinics in China were found to have grown sizably from 134 000 in 2008 to 155 000 in 2014;medical technology workers to 2.31 per clinic in 2014;and the total revenue of these clinics accounted for only 0.724% of all medical institutions,while there are more clinics in the east than the west regions in China.Conclusions The role of clinics in attracting high quality medical resources to primary care should be further enhanced for development of the hierarchical medical system in China.

Objective To establish a predictive model for digestive and respiratory infectious disease patients'selection of first-entry healthcare institutions and analyze the influencing factors,providing a reference for regional healthcare institution development.Methods The cluster sampling was used to select 1524 target patients.The data was randomly split 8∶2 into training and testing sets.The binary logistic regression method was employed to establish a predictive model for the selection of infectious disease patients'first choosing institution and analyze the influencing factors.The model's predictive performance was evaluated using the AUC of the testing set.Results It analyzed 1 524 infectious disease cases;417 chose community clinics first.Influences on their initial choice included education,insurance type,occupation,relative distance,and having a family doctor.The AUC of the test set was 0.851.Conclusion The predictive model of the selection of infectious disease patients'first choosing institution established in this study can be used to predict patient flow and help allocate medical resources reasonably.Increasing the rate of primary care for patients with infectious diseases in the region.

Objective To establish a predictive model for digestive and respiratory infectious disease patients'selection of first-entry healthcare institutions and analyze the influencing factors,providing a reference for regional healthcare institution development.Methods The cluster sampling was used to select 1524 target patients.The data was randomly split 8∶2 into training and testing sets.The binary logistic regression method was employed to establish a predictive model for the selection of infectious disease patients'first choosing institution and analyze the influencing factors.The model's predictive performance was evaluated using the AUC of the testing set.Results It analyzed 1 524 infectious disease cases;417 chose community clinics first.Influences on their initial choice included education,insurance type,occupation,relative distance,and having a family doctor.The AUC of the test set was 0.851.Conclusion The predictive model of the selection of infectious disease patients'first choosing institution established in this study can be used to predict patient flow and help allocate medical resources reasonably.Increasing the rate of primary care for patients with infectious diseases in the region.

Objective To establish a predictive model for digestive and respiratory infectious disease patients'selection of first-entry healthcare institutions and analyze the influencing factors,providing a reference for regional healthcare institution development.Methods The cluster sampling was used to select 1524 target patients.The data was randomly split 8∶2 into training and testing sets.The binary logistic regression method was employed to establish a predictive model for the selection of infectious disease patients'first choosing institution and analyze the influencing factors.The model's predictive performance was evaluated using the AUC of the testing set.Results It analyzed 1 524 infectious disease cases;417 chose community clinics first.Influences on their initial choice included education,insurance type,occupation,relative distance,and having a family doctor.The AUC of the test set was 0.851.Conclusion The predictive model of the selection of infectious disease patients'first choosing institution established in this study can be used to predict patient flow and help allocate medical resources reasonably.Increasing the rate of primary care for patients with infectious diseases in the region.

Objective To establish a predictive model for digestive and respiratory infectious disease patients'selection of first-entry healthcare institutions and analyze the influencing factors,providing a reference for regional healthcare institution development.Methods The cluster sampling was used to select 1524 target patients.The data was randomly split 8∶2 into training and testing sets.The binary logistic regression method was employed to establish a predictive model for the selection of infectious disease patients'first choosing institution and analyze the influencing factors.The model's predictive performance was evaluated using the AUC of the testing set.Results It analyzed 1 524 infectious disease cases;417 chose community clinics first.Influences on their initial choice included education,insurance type,occupation,relative distance,and having a family doctor.The AUC of the test set was 0.851.Conclusion The predictive model of the selection of infectious disease patients'first choosing institution established in this study can be used to predict patient flow and help allocate medical resources reasonably.Increasing the rate of primary care for patients with infectious diseases in the region.

Objective To establish a predictive model for digestive and respiratory infectious disease patients'selection of first-entry healthcare institutions and analyze the influencing factors,providing a reference for regional healthcare institution development.Methods The cluster sampling was used to select 1524 target patients.The data was randomly split 8∶2 into training and testing sets.The binary logistic regression method was employed to establish a predictive model for the selection of infectious disease patients'first choosing institution and analyze the influencing factors.The model's predictive performance was evaluated using the AUC of the testing set.Results It analyzed 1 524 infectious disease cases;417 chose community clinics first.Influences on their initial choice included education,insurance type,occupation,relative distance,and having a family doctor.The AUC of the test set was 0.851.Conclusion The predictive model of the selection of infectious disease patients'first choosing institution established in this study can be used to predict patient flow and help allocate medical resources reasonably.Increasing the rate of primary care for patients with infectious diseases in the region.

Objective To establish a predictive model for digestive and respiratory infectious disease patients'selection of first-entry healthcare institutions and analyze the influencing factors,providing a reference for regional healthcare institution development.Methods The cluster sampling was used to select 1524 target patients.The data was randomly split 8∶2 into training and testing sets.The binary logistic regression method was employed to establish a predictive model for the selection of infectious disease patients'first choosing institution and analyze the influencing factors.The model's predictive performance was evaluated using the AUC of the testing set.Results It analyzed 1 524 infectious disease cases;417 chose community clinics first.Influences on their initial choice included education,insurance type,occupation,relative distance,and having a family doctor.The AUC of the test set was 0.851.Conclusion The predictive model of the selection of infectious disease patients'first choosing institution established in this study can be used to predict patient flow and help allocate medical resources reasonably.Increasing the rate of primary care for patients with infectious diseases in the region.

Objective To establish a predictive model for digestive and respiratory infectious disease patients'selection of first-entry healthcare institutions and analyze the influencing factors,providing a reference for regional healthcare institution development.Methods The cluster sampling was used to select 1524 target patients.The data was randomly split 8∶2 into training and testing sets.The binary logistic regression method was employed to establish a predictive model for the selection of infectious disease patients'first choosing institution and analyze the influencing factors.The model's predictive performance was evaluated using the AUC of the testing set.Results It analyzed 1 524 infectious disease cases;417 chose community clinics first.Influences on their initial choice included education,insurance type,occupation,relative distance,and having a family doctor.The AUC of the test set was 0.851.Conclusion The predictive model of the selection of infectious disease patients'first choosing institution established in this study can be used to predict patient flow and help allocate medical resources reasonably.Increasing the rate of primary care for patients with infectious diseases in the region.