生物和功能性多病症 - - 从机制到管理
Claudia Langenberg1,2,3, Aroon D Hingorani4,5,6, Christopher J M Whitty7,8
1Precision Healthcare University Research Institute, Queen Mary University of London, London, UK. claudia.langenberg@qmul.ac.uk.
Nature medicine
|July 18, 2023
概括
全球多发病率的上升需要将重点放在专业化和通用技能上. 数据驱动的方法可以揭示各种疾病模式,并改善患者的护理.
科学领域:
- 公共卫生 公共卫生
- 临床医学 临床医学
- 医疗保健服务研究 医疗服务研究
背景情况:
- 预计全球多病性 (多种慢性疾病的同时发生) 患病率将大幅上升.
- 这种增长给患者,护理人员,医疗保健系统和社会带来了重大挑战.
- 当前的医学教育和研究往往优先考虑专业化,可能忽略了管理复杂患者需求所需的基本通用技能.
研究的目的:
- 强调需要在临床,教育和科学方法中进行范式转变,以应对日益增长的多病症挑战.
- 为了强调在专业化日益增长的情况下,保持全方位医疗技能的重要性.
- 倡导数据驱动的科学方法,以更好地理解和管理多病症的多样性.
主要方法:
- 分析不同的人口统计和生活阶段的多病症的定量和质量变化.
- 利用数据驱动的科学来量化疾病的同时发生,超出了经过充分研究的条件.
- 促进更广泛地获取跨学科和多模式数据,以整合研究.
主要成果:
- 多病症是一种异质的疾病,因年龄,种族,性别,社会经济地位和地理位置而有很大差异.
- 数据驱动的分析可以揭示多病症的病理多样性,并确定临床相关的疾病集群.
- 综合各种数据源对于全面了解多病症至关重要.
结论:
- 应对日益增长的多病症负担需要采取平衡的方法,将专业知识与强大的通用技能相结合.
- 数据驱动的科学对于阐明复杂的多病态现象和识别患者子组至关重要.
- 根据对多病症的整体理解,重新配置医疗服务,研究和临床指南是有效的,以患者为中心的护理所必需的.
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