武汉市结直肠癌筛查项目管理策略优化研究
Optimization Study of Management Strategies for Colorectal Cancer Screening Program in Wuhan City
朱静佳 1姜符亮 2刘雨晗 3邓正聪 4陶红兵1
作者信息
- 1. 华中科技大学同济医学院医药卫生管理学院 湖北 武汉 430030
- 2. 华中科技大学同济医学院第二临床学院 湖北 武汉 430030
- 3. 武汉市江夏区第一人民医院 湖北 武汉 430299
- 4. 武汉市东湖新技术开发区疾病预防控制中心 湖北 武汉 430075
- 折叠
摘要
目的 优化武汉市结直肠癌筛查项目管理策略,以降低筛查成本,提高筛查效益.方法 采用方便抽样法,选取 39 名关键知情人进行访谈.运用主题框架分析法对访谈资料进行整理分析.结果 结直肠癌筛查流程包括宣传动员、实施筛查、结果告知、诊断治疗、随访管理 5 大关键环节,存在缺乏高危人群宣传动员方案、筛查项目开展时间较短、筛查流程较为复杂、样本质量不合格、采样包损耗、忽视健康宣教、对初筛阳性居民不能持续追踪、社区和定点医院信息共享不充分、结肠镜操作规范执行不严格等问题.结论 应建立结直肠癌筛查长效机制,全面宣传动员,充分发挥基层医疗卫生机构作用,构建医院—社区闭环管理模式等.
Abstract
Objective To optimize the management strategy of colorectal cancer screening program in Wuhan,in order to reduce screening costs and improve screening benefits.Methods Convenience sampling was used to select 39 key informants for interviews.The topic framework analysis method was used to sort out and analyze the interview data.Results Colorectal cancer screening included five key links:publicity mobilization,screening implementation,result notification,diagnosis and treatment,and follow-up management.There were some problems,such as lack of publici-ty and mobilization plan for high-risk groups,short time of screening project,complicated screening process,unquali-fied sample quality,loss of sampling package,neglect of health education,insufficient continuous tracking of positive residents in initial screening,inadequate information sharing between communities and designated hospitals,and lax im-plementation of colonoscopy operation standards.Conclusion It is necessary to establish a long-term mechanism for colorectal cancer screening,fully carry out the publicity and mobilization work,give full play to the role of primary medical and health institutions,and build a hospital-community closed-loop management mode.
关键词
结直肠癌筛查/主题框架分析法/管理策略/成本效益/关键知情人访谈/卫生技术评估Key words
Colorectal Cancer Screening/Theme Framework Analysis/Management Strategy/Cost Effectiveness/Key In-formant Interviews/Health Technology Assessment引用本文复制引用
出版年
2024
NETL
NSTL
万方数据