Objective: According to ERG ( Existence Relatedness Growth) needs theory, analyze factors influencing the resignation probability in Township Health Centers (THC). Methods: Structural equation model was used based on ERG needs theory. The sample consists of 403 stuffs in the THC. Results: The result of model fitting goes well. The satisfaction levels of the needs to survive and the needs of relationship become the major influencing factors of resignation probability in the THC. Conclusion: To reduce the resignation probability in THC, it needs to guarantee their income and benefits, improve working condition and living convenience facilities.

Hierarchical diagnosis and treatment system has become one of the strategies for overcoming the diffi-culties in medical reform in our country. The important role of health information and its application in hierarchical diagnosis and treatment were thus elaborated in this paper in order to provide reference for the health information construction in establishing hierarchical diagnosis and treatment system at different levels in our country.

It is one of the important tasks to promote the development of traditional Chinese medicine culture crea-tive industry in constructing the culture-rich Shandong Province. The major factors that influence the development of traditional Chinese medicine culture creative industry in Shandong Province and the ranks of their importance were thus analyzed by questionnaire survey and hierarchy analysis, respectively. Certain suggestions were put for-ward for the development of traditional Chinese medicine culture creative industry in Shandong Province.

The paper objectively analyzes the opportunities and challenges of Internet + medical,and puts forward relevant strategies and recommendations for deeply integratingInternet +into the traditional medical industry in several aspects,including strengthening the construction of Internet infrastructure in the medical industry,regulating the market access and improving the industry standards,as well as establishing and improving relevant supporting laws,regulations and policies.

The key words, social network and author cooperation network in papers ( published in 2003-2014 ) on reform in domestic public hospitals were analyzed using Ucinet and CiteSpace visual softwares with CNKI as the data source.The current situation in reform in domestic public hospitals was revealed by mining its research hotspots, progress and author cooperation .Some suggestions were put forward for strengthening the reform in domestic public hospitals .

The distribution of authors, institutions that published papers, and key words in CNKI-covered papers on library information service model was analyzed, which showed that there are a number of high production authors in China engaged in studies on library information service model but the number of cooperative studies is few, aca-demic libraries are active in performing related studies but public libraries seldom participate in such studies, the related studies are focused on the application of information technologies and the personal demands of users.

Objective:To explore the method of selecting the supporting institutions of the national clinical medical research center by using the third-party evaluation data.Methods:Select disease fields/clinical specialties as research objects based on the criteria of having at least 5 national clinical research centers established in the field of major diseases and at least 3 established in the field of non major diseases. Collected data on the ranking of scientific and technological evaluation metrics in Chinese hospitals from the official website of the Institute of Medical Information, Chinese Academy of Medical Sciences, and collected standardized research value ranking data on the reputation ranking of Chinese hospitals and specialties from the official website of Fudan University. Based on the correspondence between the disease field/clinical specialty and the disciplines and specialties in the two major rankings, the top 5 and top 10 hospitals in the corresponding disease fields/clinical specialties in the two ranking lists were selected respectively, and the comprehensive scores of the included hospitals were calculated using the grade scoring method and ranked accordingly. Then, determine the number of hospitals to be selected based on the criteria of fully covering the recognized national clinical medical research centers supporting institutions.Results:The study focused on six disease fields/clinical specialties, including chronic kidney disease, obstetrics and gynecology, digestive system diseases, oral diseases, hematological diseases, and eye, ear, nose, and throat diseases. In the hospital ranking list formed by the top 5 hospitals included in the two rankings, a maximum of 11 hospitals needed to be included to fully cover the recognized supporting institutions, while in the hospital ranking list formed by the top 10 hospitals included in the rankings, a maximum of 6 hospitals needed to be included to achieve full coverage. Therefore, the optimal selection method was to include the top 10 hospitals in the two rankings and calculate their comprehensive scores, and select the top 6 hospitals based on their comprehensive scores.Conclusions:The selection method based on the third-party evaluation data is scientific and reliable, and can provide reference for the evaluation work of the management department of the national clinical medical research center.