Objective This study aimed to understand the needs and utilization of health services inthe years of2009,2011and2012among rural residents in XiJi City,Ningxia HuiAutonomous Region. Making the longitudinal comparison of the rural residents’ healthservice needs and utilization during the survey period and analyzing the changes and trends.The results would provide some scientific evidences and suggestions to perfect the XiJimedical health service system and improve the rural residents’ health condition.Methods Stratified random clusters sampling and homemade questionnaires were usedto select participants and collect research data in this survey in2009. And in the years of2011and2012mad the follow-up visit of the participants.Data analysis used SPSS18.0and MLwiN software to describe health service needs andutilization among participants,and multilevel model was made up to analyze the of residents’health services needs.Results The prevalence of chronic diseases in Xiji rural area were8.08%(2009),8.10%(2011) and13.54%(2012,), gender, age, ethnic, education level and marital status are themain factors affecting the prevalence. Residents suffering from chronic diseases are mainlyconcentrated in the circulatory system, motion system, digestive system, respiratory system,genitourinary system and endocrine system. The top several chronic diseases are hypertension,chronic gastroenteritis, rheumatoid arthritis Lumbar disc disease, cholecystitis and gall-stone.Two-week prevalence were12.31%(2009),16.27%(2011) and14.23%(2012). Gender,age, education level and marital status are the main factors affecting the two-week prevalence.The diseases which residents suffering from were mainly concentrated in the digestive system,motion system, respiratory system, circulatory system and urogenital system. The fluprevalence significantly increased during the survey period, prevalence of acute and chronic gastroenteritis is increasing year by year, while the cholecystitis, gallstones and hypertensionprevalence declined.Two-week outpatient visit rates was respectively6.87%(2009),9.07%(2011) and10.43%(2012); patient visit rate of47.57%,48.46%and55.45%, showed a rising trend year by year.During the investigating many patients changed their visit medical institution from the fromtownship hospitals to village clinics, which provided outpatient health services most forpatients. Residents in primary consider the distance factor when choosing a treatment agency,followed by technical factors. Residents did not see a doctor mainly because of self-treatmentand the economic hardship.Hospitalization rates of residents was respectively8.78%(2009),10.17%(2011),11.19%(2012). Patients firstly choose the county hospital as their hospitalization, secondly thetownship hospitals,thirdly the hospitals above the county level. But the township hospitalsfaced with the continual loss of the status of inpatients. Residents not hospitalization rates were19.59%in2009,16.42%in2011,12.92%in2012. Non-hospitalized mainly due to economicreasons.The multilevel model fitting result shows that factors that affect the residents of theprevalence of chronic diseases are gender, age, ethnicity, education level and marital status; thetwo-week prevalence rate was affected by gender, age, education level and marital status.Compared to the single-level model, the multi-level model is more applicable to the hierarchicaldata.Conclusion Chronic diseases become the important factor of rural residents’ healththreat; Village and township levels of medical institutions have the ability to solve farmers’common disease and frequently-occurring disease, the three-level medical institutions played animportant role in rural health service, but the quality of the services were relatively low,township level hospitals health services resources could not be utilized sufficiently; Distancebecomes the primary factor of rural residents to choose medical institutions; Economic hardship is the main factor that hampered patients could not see a doctor,especially of hospitalization;XiJi county rural residents health services needs to be influenced by gender, age, ethnic,education level and marital status. Compared with single-level model, the multi-level modelgreatly improve the fitting results in dealing with the hierarchy data. |