丹麦成年人口中患有慢性疾病的群体
Anders Stockmarr1, Anne Frølich2,3
1Department of Applied Mathematics and Computer Science, Technical University of Denmark, Lyngby, Denmark.
PloS one
|April 30, 2024
概括
多病症,具有多种慢性疾病,在丹麦使用算法绘制了地图. 确定了五个不同的患者群,通常只能通过4-5个诊断来预测,有助于个性化护理和公共卫生策略.
科学领域:
- 公共卫生 公共卫生
- 计算流行病学计算流行病学
- 医疗保健服务研究 医疗服务研究
背景情况:
- 多病症,即两个或两个以上的慢性疾病同时存在,构成了重大的公共卫生挑战,影响生活质量和增加医疗保健需求.
- 慢性疾病在多病患者群体中的基本结构和集群在很大程度上仍然没有特征,阻碍了有针对性的干预措施.
研究的目的:
- 绘制丹麦多病症人口中慢性疾病的结构.
- 使用算法方法识别不同的多病症集群.
- 探索这些已识别的集群中的社会经济和地理差异.
主要方法:
- 利用算法诊断和K-means集群算法对整个2015年丹麦多病症人口进行分析.
- 引入了"边缘数据",作为确定最佳集群数量的新方法.
- 基于流行,缺席和并发条件的特征集群,以及社会经济变量和医疗保健利用情况.
主要成果:
- 确定了五个不同的多发病群:过敏,慢性心脏病,糖尿病,高胆固醇血清,肌肉骨和精神疾病.
- 证明,对99.32%的人口的集群分配可以从4-5个诊断中确定.
- 揭示了社会经济关联,过敏群与更高的社会经济地位联系在一起,糖尿病/高胆固醇血清症群与较低的地位联系在一起. 空间变化也被注意到.
结论:
- 这项研究成功地将多病症人群划分为不同的临床相关集群.
- 研究结果表明,有可能改善基于个人的护理,预防策略和临床指导方针的制定.
- 鉴定到的集群及其特征为更好地管理多病症人口提供了基础.
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