Development of multimorbidity patterns in older adults in Switzerland: A competing risks modeling approach

This is the authors' abstract. We don't add key points for this paper.

Multimorbidity, multiple long-term health conditions co-occurring in one individual, is a complex challenge that affects individuals, healthcare systems, and society. People with multimorbidity have a lower quality of life, higher mortality, and more complex needs and holistic treatments, resulting in higher health insurance and overall healthcare costs. Our study aims to investigate the progression of multimorbidity by identifying the main disease patterns in the adult population. Using an extensive dataset of health insurance claims from one of the largest Swiss health insurance companies, we categorize chronic long-term diseases into different pharmacy cost groups based on a medical classification system to assess the morbidity status of insureds. Developing on a competing risks framework, we use subdistribution hazard models adjusted for age effects to model key multimorbidity patterns, considering the most prevalent chronic diseases in the population. Our analysis focuses on estimating cumulative incidence functions for gender-specific trajectories. By shedding light on these patterns, our study contributes to a deeper understanding of multimorbidity dynamics and potential patient pathways. It provides information for decision-makers, financial planners, and healthcare professionals to enable optimal resource allocation and facilitate prevention and interventions tailored to the needs of various morbidity groups to reduce the disease burden and economic impact.