中国全科医学 ›› 2023, Vol. 26 ›› Issue (16): 1965-1971.DOI: 10.12114/j.issn.1007-9572.2022.0634

• 论著·基层卫生服务研究 • 上一篇    下一篇

广东省基层医疗卫生机构诊疗人次变化及影响因素的灰色关联分析

徐碧霞1, 姚卫光2,*()   

  1. 1510405 广东省广州市,广州中医药大学第一附属医院
    2510515 广东省广州市,南方医科大学卫生管理学院
  • 收稿日期:2022-11-15 修回日期:2023-01-22 出版日期:2023-06-05 发布日期:2023-03-02
  • 通讯作者: 姚卫光

  • 作者贡献:徐碧霞、姚卫光负责文章的构思与设计、研究的实施与可行性分析、论文的修订、文章的质量控制及审校;徐碧霞负责数据收集与整理、统计学处理、结果的分析与解释、论文撰写;姚卫光对文章整体负责,监督管理。
  • 基金资助:
    广东省高校哲学社会科学重点实验室:公共卫生政策研究与评价资助项目(2015SWSYS0010); 广州公共卫生服务体系建设研究基地资助项目(2021—2023); 广州市哲学社科规划2021年度课题(2021GZYB10); 广东省卫生经济学会2022年度面上课题资助项目(2022-WJMZ-44)

Changes in Patient Visits and Associated Determinants in Primary Healthcare Settings in Guangdong: a Grey Relational Analysis

XU Bixia1, YAO Weiguang2,*()   

  1. 1The First Affiliated Hospital of Guangzhou University of Chinese Medicine, Guangzhou 510405, China
    2School of Health Management, Southern Medical University, Guangzhou 510515, China
  • Received:2022-11-15 Revised:2023-01-22 Published:2023-06-05 Online:2023-03-02
  • Contact: YAO Weiguang

摘要: 背景 我国分级诊疗制度建设已取得一定成效,但基层医疗卫生机构发展速度依旧相对缓慢。 目的 分析2013—2020年广东省基层医疗卫生机构诊疗人次的变化情况及影响因素,为政府深化分级诊疗制度建设提供参考依据。 方法 于2021年12月,从2013—2015年《广东省卫生统计年鉴》、2016—2017年《广东省卫生和计划生育统计年鉴》、2018—2020年《广东省卫生健康统计年鉴》提取基层医疗卫生机构诊疗人次数据,作为参考序列;从《广东统计年鉴2021》提取人口数据及居民人均可支配收入,从2015—2017年《中国卫生和计划生育统计年鉴》和2018—2021年《中国卫生健康统计年鉴》提取基层医疗卫生机构财政补助收入和医疗保险参保人数,作为比较序列。采用灰色关联分析法评价各影响因素与基层医疗卫生机构诊疗人次的关联强度。 结果 2013—2019年,广东省医院诊疗人次从33 459.2万人次增长至40 131.7万人次,年均增长3.08%,同期全省基层医疗卫生机构诊疗人次年均增长2.10%,2019年全省基层医疗卫生机构诊疗人次已达43 731.7万人次。2020年受新型冠状病毒感染疫情的影响,医院和基层医疗卫生机构的诊疗人次均有明显下降,医疗机构总诊疗人次中基层医疗卫生机构诊疗人次的占比从2013年的50.7%下降至2020年的48.1%。灰色关联分析结果显示,常住人口(r=0.913)及65岁以上人口(r=0.913)与基层医疗卫生机构诊疗人次关联度最强,其次是城乡居民基本医疗保险参保人数(r=0.899)、基层医疗卫生机构床位数(r=0.893)、基层医疗卫生机构数(r=0.886)和城镇职工基本医疗保险参保人数(r=0.872)。 结论 目前,仍有较多患者选择至医院就诊,基层首诊制有待加强,建议结合人口老龄化的社会背景,从丰富基层卫生服务内涵、拉开不同级别医疗机构的医保支付差距、提升基层医疗卫生机构服务能力三方面满足居民就近就医的服务需求。

关键词: 分级诊疗, 基层医疗卫生机构, 诊疗人次, 灰色关联分析, 影响因素分析

Abstract:

Background

China has made some achievements in the construction of hierarchical medical system, but the development of its primary healthcare settings is still relatively slow.

Objective

To analyze the changes in patient visits and associated determinants in primary healthcare settings in Guangdong during 2013 to 2020, providing a basis for deepening the construction of hierarchical medical system.

Methods

In December 2021, this study extracted patient visits in primary healthcare institutions of Guangdong from Guangdong Health Statistics Yearbook (2013—2015), Guangdong Health and Family Planning Statistical Yearbook (2016—2017), and Guangdong's Hygiene and Health Statistical Yearbook (2018—2020) as the reference sequence, and extracted the population data and per capita disposable income from Guangdong Statistical Yearbook 2021, and the financial subsidy for primary healthcare institutions and the number of medical insurance participants from China Health and Family Planning Statistical Yearbook (2015—2017) and China's Hygiene and Health Statistical Yearbook (2018—2021) as the comparative sequence. Grey relational analysis was used to evaluate the strength of correlation between the number of patient visits and its potential associated determinants involving demographic and socioeconomic status, health resource allocation and medical insurance participation.

Results

The number of hospital visits in Guangdong increased from 334.592 million in 2013 to 401.317 million in 2019, with an average annual growth of 3.08%. The number of patient visits in primary healthcare settings in the province reached 437.317 million in 2019, and the average annual growth in these settings was 2.10% during 2013 to 2019. In 2020, the number of patient visits in hospitals and in primary healthcare settings both decreased significantly because of the COVID-19 pandemic. The number of patients visits in primary healthcare settings accounted for 50.7% of all patients visits in medical institutions in 2013, which declined to 48.1% in 2020. Grey relational analysis showed that both the number of residents (r=0.913) and the number of people aged over 65 years old (r=0.913) had the strongest correlation with the number of patient visits in primary healthcare settings, followed by the number of urban-rural resident basic medical insurance participants (r=0.899), the number of beds in primary healthcare settings (r=0.893), the number of primary healthcare settings (r=0.886) and the number of urban employee basic medical insurance participants (r=0.872) .

Conclusion

At present, many patients still choose to hospitals for medical services, which calls for actions to strengthen the first contact in primary care system. It is suggested to meet the needs of residents for nearby medical treatment by enriching the connotation of primary care services, widening the gap of healthcare expenses reimbursed by medical insurance among medical institutions and improving the service capacity of primary healthcare settings under the background of population aging.

Key words: Hierarchical diagnosis, Primary healthcare institutions, Medical attendances, Grey correlation analysis, Root cause analysis