Characterization of complex multimorbidity patterns through network models: epidemiology and impact on mortality and health services use
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University of Cadiz Spain
Publication date: 2023-04-26
Popul. Med. 2023;5(Supplement):A1868
Multimorbidity has been defined as the presence of two or more chronic diseases, and is associated with reduced quality of life, increased disability, greater functional impairment, increased health care utilization, and increased mortality. Thus, understanding its epidemiology and inherent complexity is essential to improve the quality of life of patients and to reduce the costs associated with this condition. Through this study we aim to characterize multimorbidity patterns and later describe their impact on mortality and health service use through a network science approach.

Using a large dataset of 1.5 million health records on chronic diseases from 2014 to 2021, and combined with mortality and use of health care services data, we explore the application of mixed graphical models and its combination with social network analysis techniques for the detection and profiling of complex multimorbidity patterns.

We found large age differences between multimorbidity patterns, with respiratory, mental and addiction patterns in the younger groups, while in the older groups the chronic disease profiles identified were mainly muscular, cardiovascular, and complex. Mental health patterns presented a higher prevalence among women. Geographic differences were also observed by county and in the use of services and mortality, with cardiovascular and complex patterns being the more prevalent in poorer neighborhoods.

Our initial findings demonstrate the suitability and usefulness of this approach for the study of multimorbidity based on the use of disease networks, which offer both the researcher and health professionals a holistic and organic view of the relational structure of chronic disease. This analytical approach offers methodological advantages for working with complex data sets and with high dimensionality, as well as a better measurement of the impact of multimorbidity on mortality and health services.