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Analysis Utilization And Influencing Factors Of Community Medical Service In Ningbo

Posted on:2011-07-12Degree:MasterType:Thesis
Country:ChinaCandidate:H F XinFull Text:PDF
GTID:2144360305958101Subject:Public Health
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Research Background and ObjectiveIn recent years, as more emphasis and support have been given to community health service by the government and the society, the community health service has sustained rapid development. The research, conducted both domestically and abroad, indicates that community health service is the best system to meet basic health needs of urban and rural residents, has a clear advantage in providing convenient, continuous, comprehensive, coordinated and affordable health service [1], and not only contributes in promoting the fairness, accessibility and efficiency of health care service but also plays an effective role in controlling healthcare cost increases and in improving the health standard for people. Thus the further development of community health service and the enhancement of the community health service utilization by the urban and rural residents have been gradually become the focus of study at all levels of administrations.By the investigation on the status of use of community-based health service institution in Ningbo, this study aims to understand the status of use of community-based health service institution among urban and rural residents, analyze the influencing factors, promptly monitor the trend in longitudinal and transverse directions, know and evaluate the influencing factors properly, and then propound the related constructive suggestions to promote the use of community-based health service institution, to increase the utilization rate of community-based health service institution among urban and rural residents, at the same time, to provide the theory basis and the detailed and basic information for government policy making, the implementation of medical reform and the reform of health institution in Ningbo. MethodsThe case study is the city of Ningbo. The related data for Ningbo City is from the Fourth National Health Service Survey, and the multi-stage stratified random sampling method is used to conduct the survey, for which Yuyao City and Fenghua City are selected for rural sample and Jiangdong District is selected for urban sample. Five townships (towns or neighborhoods) are randomly selected from each sample city or district, two villages (or residential committees) are randomly selected for each township (or neighborhood), and, in proportion to urban and rural population,60 households are chosen for each village in Fenghua City,90 households are chosen for each village in Yuyao City and 40 households are chosen for each residential committee in Jiangdong District. In total,1900 households consisting of 5248 people are selected from 30 villages (or residential committees) in 15 townships (or neighborhoods) in three cities or district in the City. The survey is conducted through home visit method, and the main contents of the survey are general family data, demographic characteristics, medical conditions and health service accessibility. This paper uses 178 people seeking treatment at community health service agencies among 319 people, who fell sick in two weeks during the survey, as study subjects, and the study provides information on the (?)tilization and related factors of community health service agencies by urban and rural residents in Ningbo City. The x2 analysis is used for the single-factor analysis of the community health service utilization factors and the Logistic regression model is used for the multi-factor analysis of the community health service utilization factors. Survey data are analyzed using the statistical package SPSS 17.ResultsAmong 319 people who fell sick in the two weeks,178 people sought treatment at urban or rural community health service agencies, a percentage of 55.80%,58.82% among urban residents and 54.00%among rural residents; the utilization rate by male residents is 57.60%and is 54.04%by female residents; the utilization of the community health service for various marital status is 52.31%-60.63%, in terms of education level, the utilization rate is highest with education of high school/secondary technical school at 71.05%and is lowest with education of junior high school at 50.60%, in terms of age groups, the utilization rate is highest among the over 65 group; in terms of income level, the utilization rate is highest for those earning less than 5000 Yuan at 68.97%and is lowest for those earning between 5000 Yuan and 10000 Yuan at 46.58%; in terms of insurance policy, the utilization rate is 62.75%for those participating in Urban Worker Insurance and is 42.11%for those without insurance; in terms of closeness for treatment, those living within one kilometer are more likely to seek treatment at the community health service agencies with utilization rate of 57.95%; the main reason for the choice of community health service agencies is the proximity, the utilization rate is 74.51%for those living nearby, the rate is lowest at 21.25%for those seeking personnel with high level of expertise; the utilization rates of the community health service agencies are 74.51%and 59.49%for those sensing the illness is not serious and common, respectively, and the utilization rate is 32.88%for those sensing the illness is serious. The single-factor 2 analysis is used for region, gender, and age, the result shows that the main impact factors affecting the treatment at the community health service are the perceived seriousness of illness and the main reason for the choice of institution; further analysis using logistic analysis shows that the impact factors are the perceived seriousness of illness and the main reason for the choice of treatment. (B are 0.853 and 0.861 respectively and the significance levels are both 0.00.)Conclusion and SuggestionCompared to 25.9%in 2003, the utilization of the community health service agencies in Ningbo City by urban and rural residents has a significant increase, rising to 39.18%, rising from 32.88%to 51.26%for urban region and from 24.10%to 32.00%for rural region (in order to compare with 2003, some patients in stations are excluded), the utilization of both urban and rural community health service has increased, which indicates that the policy of strengthening community health service system by the government to improve the accessibility of the community health service has achieved some success.The factors affecting the utilization of community health service agencies by urban and rural residents are:the main reason for the choice of treatment and the perceived seriousness of illness. Convenient proximity will increase the utilization of the community health service agencies by residents; in addition, those residents who perceive that the illness is not serious or common are more likely to seek treatment at community health service agencies.The urban and rural community health service in Ningbo has gained a certain degree of utilization by residents, but compared with the 90%utilization of community health service for overall medical and health care service in developed countries, there is some gap, and therefore there is some room for significant increase in the utilization of community health service; as a developed region in economy, Ningbo needs to introduce a variety of measures to develop the community health service greatly and to improve the utilization of the community health service continuously. We propose to adopt differential developments to gradually establish the community health service with special characteristics, to introduce a variety of measures to vastly raise the professional level of medical service personnel at community health service agencies, to expand publicity to continuously increase the awareness and reputation of the community health service, and to implement new policies to steadily guide residents to seek treatment at the community health service agencies.
Keywords/Search Tags:Health Services Survey, community health service, Health Servicesutilization, Influencing factors, Logistic Regression model
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