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目的探讨2010~2013年乳山市农村高血压卫生服务利用的变化,分析卫生服务利用的影响因素进而明确人群健康和卫生服务利用存在的问题。方法通过2010年基线调查和2013年结局调查收集抽样人群数据。利用分层随机抽样的方法对乳山市农村高血压患者进行问卷调查,比较分析干预前后卫生服务利用指标;采用非条件Logistic回归对干预前后的卫生服务利用的影响因素进行分析。结果调查2 993人,高血压患者1 197例,男性527例;女性670例。主要就诊单位是村卫生室和乡镇卫生院,二者约占75%;选择医疗机构的主要原因为距离住所近、方便的比例占到了70%以上;高血压患者4周就诊率性基线调查为49.18%,而结局调查为50.22%(P>0.05);高血压服药率分别为49.91%和58.44%(P<0.05);高血压住院率分别为4.84%和7.57%,高血压应住院而未住院率分别为35.80%和17.02%。干预前主要影响高血压患者住院的因素有个人收入的高低、有无并发症(P<0.05),其中有并发症的OR值为12.55,高收入组OR值为5.25;干预后高血压患者住院的影响因素有性别、有无并发症、收入情况,有无并发症的OR值为15.07,中低收入组的OR值为5.07,中高收入组为4.96;性别的OR值为0.14。结论干预后影响高血压住院卫生服务利用的因素有性别、个人收入、患病年数和并发症。
Objective To explore the changes of utilization of health services in rural areas in Rushan from 2010 to 2013, analyze the influencing factors of utilization of health services and clarify the existing problems of population health and utilization of health services. METHODS: Sampling population data were collected from the 2010 baseline survey and the 2013 outcome survey. The stratified random sampling method was used to survey the rural hypertensive patients in Rushan City. The health service utilization indexes before and after the intervention were compared and analyzed. The non-conditional Logistic regression was used to analyze the influencing factors of the health service utilization before and after the intervention. Results A total of 2 993 people were surveyed, 1 197 hypertensive patients, 527 males and 670 females. The main treatment units are village clinics and township hospitals, accounting for about 75% of all cases. The main reason for choosing medical institutions is that they are near to their dwelling places, accounting for more than 70% of them. The baseline survey of 4-week visits for hypertensive patients is 49.18%, respectively, while the outcome was 50.22% (P> 0.05). The rates of taking hypertension were 49.91% and 58.44% respectively (P <0.05). The rates of hypertension were 4.84% and 7.57% Hospitalization rates were 35.80% and 17.02% respectively. Intervention before the main factors affecting the hospitalization of patients with hypertension have personal income levels, with or without complications (P <0.05), of which complications OR was 12.55, OR of high-income group was 5.25; hospitalized hypertensive patients after intervention The odds ratio was 15.07 for the gender, with or without complication, income status, with or without complication, 5.07 with the middle and low income group, and 4.96 with the middle and high income group. The odds ratio for the sex was 0.14. Conclusions The factors influencing the utilization of hospital inpatient services after hypertension are gender, personal income, number of years of illness and complications.