估计英格兰诊断不足的负担:对链接的初级保健数据的建模研究
Olga Anosova1, Anna Head1, Brendan Collins1
1Department of Public Health, Policy and Systems, University of Liverpool, Liverpool, United Kingdom.
估计英格兰未诊断的慢性疾病显示,在条件和人口统计学方面存在显著的差异. 低诊断率随着时间的推移而下降,但与贫困没有一致的相关性,也没有显示统一的空间模式.
科学领域:
- 公共卫生 公共卫生
- 流行病学 流行病学
- 医疗信息学 医疗信息学
背景情况:
- 未被诊断的慢性疾病对健康构成重大风险,并导致健康不平等.
- 估计低诊断率对于了解疾病负担和差异至关重要.
研究的目的:
- 估计英格兰11种常见慢性疾病的诊断不足的发生率.
- 分析跨社会人口统计学因素和地理区域的诊断不足的变化.
主要方法:
- 利用了130万名患者 (2008-2020) 的相关初级保健,医院和死亡率数据.
- 开发了一个动态状态模型,以根据诊断,死亡率和病例死亡率来估计低诊断.
- 分析了根据年,性别,年龄,贫困和行政区域的不足诊断,并应用了小区域估计.
主要成果:
- 低诊断因病情而有很大差异 (2018年中风为16%,前列腺癌为69%).
- 总体而言,在研究期间,诊断不足的情况有所减少.
- 贫困地区缺乏诊断的持续集中;模式因情况和地区而异.
结论:
- 低诊断在疾病之间并不是由剥夺或空间模式均分布的.
- 新的估计方法凸显了对低诊断驱动因素的进一步研究的需要.
- 这些发现强调了在公共卫生战略中解决不足诊断的复杂性.
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