Multimorbidity Patterns at Older Ages: A Study Using Graphical Model and Network Analysis

Hoang Khanh Linh Dang , Alma Mater Studiorum - Università di Bologna
Rossella Miglio, Università di Bologna
Rosella Rettaroli, Università di Bologna
Giulia Roli, University of Bologna

One key factor to construct appropriate healthcare planning for sustainable aging populations is the possibility of identifying precise multimorbidity patterns at older ages and seizing their progression (trajectories) in time. In both developed and developing countries, understanding the structure of multimorbidity, and most ideally across time, is an urging challenge in order for groups who share the same degree of vulnerability and needs to receive assistance and intervention in a timely manner. Compared to traditional approach in literature like factorial and clustering analysis, the combination of probabilistic approach from graphical model and intuitive visualization from network analysis is emerging quickly as powerful tool in recent years to not only efficiently explore the richness of administrative health data, but also to provide an analysis framework whom predictability can be assessed. Applying these methods on longitudinal data of individuals aged 50 and above residing Emilia-Romagna region (northern Italy) in 2011 and followed up to 2019, we study the multimorbidity patterns at older ages, their changes across time, and the profiles of patients within identified patterns.

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 Presented in Session 64. Wellbeing in Older Age