OBJECTIVE:To provide the basis for the revision of appendices of volume Ⅰ and Ⅱ of Chinese Pharmacopoeia (2005 edition).METHODS:The general standards of preparations and the examinational methods in the appendices of volume Ⅰ and Ⅱ of Chinese Pharmacopoeia (2005 edition) were compared and analyzed in order to find out the problems.RESULTS:Volume Ⅰ was different from volume Ⅱ in the respect of numbers,ordering,subtypes,examinational items of preparations and the kinds,contents of examinational methods.In addition,the specification,the consistency of standard and the advancement of technological level were not in line with the standards.CONCLUSION:The appendices of volume Ⅰ and Ⅱ of Chinese Pharmacopoeia (2005 edition) should be revised.

Objective By comparing the medical complaints and disputes between the two tertiary general hospitals in Beijing and Lhasa, this paper proposed on how to build a harmonious doctor-patient relationship.Methods A study of annual reports of these two hospitals analyzed descriptively patient complaint rate, rate of medical disputes registered for court jurisdiction, makeup of medical disputes, and their solutions.Results In 2016, the patient complaint rate, and rate of medical disputes registered for court jurisdiction were 3.5/10 000 and 12.4/10 000 respectively, much higher than 0.8/10 000 and 1.1/10 000 of the Lhasa counterpart hospital.A significant gap was also found in the makeup of medical disputes, their solutions, and role of hospital leadership between the two hospitals.Conclusions Beijing is recommended to appoint hospital leader on duty, to assist in handling medical complaints and disputes, and ease doctor-patient contradictions.Lhasa is recommended to improve the medical dispute handling mechanism, improve medical service competency and management.

Objective? To evaluate the effects of competency-based training model in training for new nurses. Methods? Randomized controlled trials and quasi experiments on application of competency-based training model in training for new nurses were retrieved in PubMed, EMBASE, Cochrane Library, Web of Science, Chinese National Knowledge Infrastructure (CNKI), China Scientific Journal Database, Wanfang Data and VIP by computer. Meta-analysis was carried out with the RevMan 5.3 after literature screening, data extraction and quality assessment of literature. Results? A total of 6 literatures were included. Meta-analysis showed that competency-based training model could improve the knowledge comprehensive capacity [MD=4.91, 95%CI(3.84, 5.99), P＜ 0.001], good personal qualities [MD=0.28,95%CI(0.22,0.35),P＜0.001], interpersonal communication skills [MD=2.31, 95%CI(0.84, 3.78), P=0.002], clinical nursing ability [MD=0.33, 95%CI(0.08, 0.58), P=0.040], construction and development ability of specialty [MD=0.23, 95%CI(0.19, 0.27), P＜ 0.001], critical thinking and innovation ability [MD=1.37, 95%CI(0.17, 2.57), P=0.020]. Conclusions? Competency-based training model in training can effectively improve new nurses' knowledge comprehensive capacity, good personal qualities, interpersonal communication skills, clinical nursing ability, construction and development ability of specialty, critical thinking and innovation ability, and improve their competency. The multicenter, high quality and large-sample study on effects of competency-based training model in training for nurses should be carried out since number of the included literatures involving evaluation indexes of this study was few and heterogeneity occurred in some evaluation indexes.

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.