Abstract
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.
Published Version
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