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The Study On The Status And Requirement Forecast Of The Health Manpower In Jiangsu Province

Posted on:2007-12-15Degree:MasterType:Thesis
Country:ChinaCandidate:L L ChenFull Text:PDF
GTID:2144360185978342Subject:Epidemiology and Health Statistics
Abstract/Summary:PDF Full Text Request
Objective: In order to provide scientific information for projecting health human resource, this study, by analyzing the status of health manpower resource(HMR) of Jiangsu province, was trying to find out the problems which have existed in the health manpower resources(HMR) of Jiangsu province and propose the corresponding countermeasures. Then the feasible forecasting models that adapted to the development of HMR in Jiangsu province were established on the base of current status and used to forecast the number of the future health personnel (HP) in Jiangsu province in 2008, 2010, 2015.Method: The descriptive study of epidemic was used in analyzing amount and structure of HMP, the emphases were structure of specialty, age, education, technical post and area district ; the dynamic trends of the HMP for its development during 1975-2003 was analyzed. The demands of HP were estimated and predicted by 4 statistical models which were ARIMA, Grey(1,1),quadratic multinomial regress model and weight average combination model. In the meantime, Hospital Planning Model as a typical method was used to forecast HP too.Result: The data showed that there were 279583 health personnel in total in Jiangsu province ,including 219538 health technological personnel (HTP, 78.52%). 80.07% of HP were in city, 19.93% were in country. The number of HTP, doctors and nurses per 1000 persons on average were 3.40, 1.45 and 1.03 respectively. The ratio for doctor and nurses was 1:0.64. 58.12% of HTP are centralized in hospitals. The numbers of HTP per 1000 persons in the south area, the middle area and the north area of Jiangshu province were 4.88, 3.19, 2.50 persons respectively. The proportion of graduate students...
Keywords/Search Tags:health manpower, status analyze, requirement forecast, weight average combination model
PDF Full Text Request
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