利用贝叶斯空间建模,探索与2型糖尿病疾病管理计划的退出相关的区域和社会人口差异
B Kauhl1, M Vietzke2, J König2
1AOK Nordost - Die Gesundheitskasse, Potsdam, Germany. boris.kauhl@nordost.aok.de.
Research in health services & regions
|August 23, 2024
概括
德国的2型糖尿病 (T2DM) 疾病管理计划具有显著的区域非注册差异. 干预措施应针对弱势群体,包括具有较低社会经济地位和外国国籍的人群,以改善T2DM护理.
科学领域:
- 公共卫生 公共卫生
- 医疗保健服务研究 医疗服务研究
- 流行病学 流行病学
背景情况:
- 针对2型糖尿病 (T2DM) 的疾病管理计划 (DMP) 是德国最大的.
- 了解区域入学差异对于优化T2DM护理至关重要.
- 在T2DM DMP中识别代表性不足的人口是一个公共卫生优先事项.
研究的目的:
- 分析德国T2DM DMP退学率的区域差异.
- 确定与T2DM DMP退学相关的社会人口统计因素.
- 确定需要针对性干预的特定地理区域和人口群体.
主要方法:
- 利用了170万名AOK Nordost医疗保险持有者的数据.
- 采用贝叶斯空间建模 (贝萨格-约克-莫利和空间变量系数模型) 进行分析.
- 应用空间扫描统计 (SaTScan) 来检测未注册个体的集群.
主要成果:
- 2019年,36.8%的T2DM患者没有被纳入DMP,区域差异很大.
- 高失学率集中在梅克伦堡-西波梅兰和柏林.
- 不登记与女性性别,年龄较小,失业,外国国籍,家庭规模较小和通勤模式有关.
结论:
- 较低的社会经济地位和外国国籍始终与T2DM DMP不入学有关.
- 目前的T2DM DMP没有有效地接触到高风险人群,可能会增加可预防的住院治疗.
- 未来的干预措施必须优先考虑这些服务不足的群体在已确定的高风险地区.
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