中国全科医学 ›› 2024, Vol. 27 ›› Issue (31): 3877-3883.DOI: 10.12114/j.issn.1007-9572.2023.0714

• 论著 • 上一篇    下一篇

不同年龄段就诊居民社区卫生服务的反应性评价现状与影响因素研究

施译楠, 周驰*()   

  1. 311121 浙江省杭州市,杭州师范大学公共卫生学院健康管理系
  • 收稿日期:2024-01-19 修回日期:2024-04-23 出版日期:2024-11-05 发布日期:2024-08-16
  • 通讯作者: 周驰

  • 作者贡献:

    施译楠负责文章构思与整体框架设计,统计学处理,图、表的绘制与展示,论文起草;周驰提出研究思路,设计研究方案,负责研究过程的实施、论文的修订、文章的质量控制与审查,对文章整体负责、监督管理。

  • 基金资助:
    国家自然科学基金面上项目(72274050); 教育部人文社会科学研究青年基金(22YJCZH262)

Responsiveness Assessment and Its Influencing Factors of Community Health Services among Residents of Different Ages

SHI Yinan, ZHOU Chi*()   

  1. School of Public Health, Hangzhou Normal University, Hangzhou 311121, China
  • Received:2024-01-19 Revised:2024-04-23 Published:2024-11-05 Online:2024-08-16
  • Contact: ZHOU Chi

摘要: 背景 反应性作为卫生系统绩效评价的重要目标,是提高基层卫生服务能力的重要依据,目前许多研究将反应性与满意度的概念混淆,对反应性的评价不够全面,注重研究反应性水平忽视了反应性分布。 目的 了解浙江省不同年龄段就诊居民对社区卫生服务的反应性评价现状,并分析其影响因素。 方法 采用立意抽样与方便抽样相结合的方法,于2022年7—8月选取浙江省杭州市和台州市的6家社区卫生服务中心作为调查现场,对门诊就诊居民进行反应性量表调查;采用WHO推荐的反应性8个部分的权重计算反应性总体水平和分布,采用单因素分析和多元线性回归分析探讨不同年龄段居民对社区卫生服务的反应性评价的影响因素。 结果 浙江省就诊居民对社区卫生服务的反应性评分为(8.31±1.04)分,反应性分布指数为0.13;各年龄段就诊居民均对尊严与社会支持维度评分较高,分别为(8.60±1.24)分和(8.63±1.20)分,对选择性和自主性维度评分较低,分别为(7.96±1.56)分和(8.04±1.34)分。户口是青年人对社区卫生服务的反应性评价的影响因素,文化程度和月收入是中年人对社区卫生服务的反应性评价的影响因素(P<0.05)。 结论 浙江省社区卫生服务的反应性总体水平较高且分布较均衡,需对城镇户口的青年人、大专/本科及以上的中年人的社区卫生服务需求及反应性多加关注。基层社区卫生服务中心在让患者获取医疗健康服务方案信息以及自由选择社区医生/护士方面还有待提高,以更好满足居民合理的卫生健康服务需求。

关键词: 社区卫生服务, 反应性, 横断面研究, 影响因素分析, 多重线性回归

Abstract:

Background

Responsiveness is a key goal in evaluating the performance of the health system, and is also an essential basis for improving the capacity of primary health services. Currently, many studies confuse the concepts of responsiveness and satisfaction, and the evaluation of responsiveness is not comprehensive enough, focusing on the level of responsiveness but ignoring its distribution.

Objective

To understand the responsiveness evaluations of community health services among residents of different ages in Zhejiang province and to analyze its influencing factors.

Methods

Utilizing the method of purposive sampling and convenience sampling, six community health service centers in Hangzhou and Taizhou, Zhejiang province, were selected as the investigation sites from July to August 2022 to assess the responsiveness scale of outpatient residents. The weights of the eight components of responsiveness recommended by the WHO were used to calculate the overall level and distribution of responsiveness. Univariate analysis and multiple linear regression were used to explore the influencing factors on the responsiveness level among residents of different ages.

Results

The score of responsiveness for community health services in Zhejiang was (8.31±1.04) points, and the responsiveness distribution index was 0.13; residents of different age groups expressed their higher satisfaction with the dimensions of dignity and social support, with scores of (8.60±1.24) points and (8.63±1.20) points, respectively. In contrast, the dimensions of selectivity and autonomy received lower ratings, with scores of (7.96±1.56) points and (8.04±1.34) points, respectively. Household registration was an influencing factor for responsiveness evaluation of community health services among young people, while education level and monthly income were influencing factors for responsiveness evaluation among middle-aged individuals (P<0.05) .

Conclusion

The overall level of community health service responsiveness in Zhejiang province is good, and the distribution is more balanced. More attention should be paid to the demand and responsiveness of community health services among young people with urban household registration and middle-aged people with a college/bachelor's degree or above. Primary care community health service centers still need to improve in providing patients with access to information about health service plans and the freedom to choose community doctors/nurses, thereby better satisfying the reasonable healthcare service demands of residents.

Key words: Community health services, Responsiveness, Cross-sectional studies, Root cause analysis, Multiple linear regression

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