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| 投稿时间： 2015-04-03 最后修改时间： 2015-05-18 摘要点击次数: 2658 全文下载次数: 1343 |
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| 引用本文：武娜娜, 李程跃, 胡敏,等.我国县级疾病预防控制中心效率影响因素的多水平分析[J].中国卫生政策研究,2015,8(5):73-78 |
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| 武娜娜1,2, 李程跃1,2, 胡敏2,3, 励晓红1,2, 李晓姣1,2, 姜立文1,2, 郝模1,2 |
1. 复旦大学卫生发展战略研究中心 上海 200032;
2. 健康风险预警治理协同创新中心 上海 200032;
3. 复旦大学公共卫生学院 上海 200032 |
| 基金项目:国家自然科学基金(71373004、71303058);教育部人文社会科学研究青年基金(12YJCZH100);教育部创新团队项目(IRT_13R11) |
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| | 摘要:目的: 探讨我国县级疾病预防控制中心(简称“疾控中心”)效率的影响因素.方法:全国系统抽样选取458个县级样本疾控中心,运用多水平模型对2012年数据进行分析,明确区域层面(高水平)和机构层面(低水平)因素对机构效率的影响.结果: 我国县级疾控中心的效率在省份间存在聚集性,区域层面的人口密度对机构效率存在影响,机构层面中卫生技术人员比例、人均服务收入、人均实验室面积对效率有显著影响.结论:区域层面和机构层面的因素均对效率产生影响,多水平模型有助于全面认识我国疾控中心效率的影响因素. | |
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关键词:疾病预防控制中心 多水平模型 影响因素 效率
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| Influencing factors on the efficiency of county-level centers for disease control and prevention in China via multilevel modeling |
| WU Na-na1,2, LI Cheng-yue1,2, HU Min2,3, LI Xiao-hong1,2, LI Xiao-jiao1,2, JIANG li-wen1,2, HAO Mo1,2 |
1. Research Institute of Health Development Strategies, Fudan University, Shanghai 200032, China;
2. Collaborative Innovation Center of Social Risks Governance in Health, Shanghai 200032, China;
3. School of Public Health, Fudan University, Shanghai 200032, China |
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| | Abstract:Objective: To examine the influencing factors of the efficiency of county-level centers for disease control and prevention (CDCs) in China. Methods: 458 county-level CDCs were selected based on a systematic sampling method. Multilevel modeling was used to analyze the region-level and institution-level influencing factors affecting the efficiency of CDCs. Results: It was found that the region (province) is associated with the efficiency of a CDC. The region-level factor of population density exhibited a significant influence, while the institution-level factors such as the proportion of health technicians, service income and CDC laboratories per capita also had an influence on overall efficiency. Conclusions: Both the region-level and institution-level determinants influence efficiency. Multilevel modeling can help researchers gain a comprehensive understanding of the influencing factors that affect the CDC efficiency. | |
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