Multimorbidity is significantly associated with life quality decline, disability, and increased mortality risk. Additionally, it leads to greater consumption of healthcare resources, presenting substantial challenges to healthcare systems globally. To better assess the burden of multimorbidity, its impact on patient health outcomes and healthcare services, and to explore the underlying mechanisms in its development, this paper summarizes the existing methods used for measuring and analyzing multimorbidity in research and practice, including disease count, disease-weighted indices, multimorbidity pattern recognition (such as disease association analysis, clustering analysis, and network analysis) and longitudinal methods to provide references for the accurate assessment of the prevalence of multimorbidity and its changes and improve the validity and universality of research findings.
共病与生活质量下降、功能障碍和死亡风险增加显著相关,还可导致更大程度的卫生保健资源消耗,对全球范围内卫生保健体系带来了巨大挑战。为更好地评估共病的疾病负担、共病对患者健康结局和卫生服务的影响以及探索共病形成机制,本文综述了现有研究和实践中使用的共病测量与分析方法,包括疾病计数、疾病加权指数、共病模式识别(如疾病关联分析、聚类分析和网络分析等)及共病的纵向测量与分析方法。旨在为准确评估共病的患病状况和变化情况提供参考,以提高研究结果的有效性和普遍性。.