Methodological complexity may be a barrier to developing tools for multimorbidity risk prediction. Prognostic prediction models estimate patients’ risk of disease incidence, typically for a single disease independent of other chronic diseases incidence. When estimating the risk of multiple chronic diseases, these models fail to describe the dependence between the incidence of multiple diseases leading to inaccurate perceptions of risk.

This webinar presents a copula-based model to estimate the risk of the incidence of multiple chronic diseases, while accounting for the dependence that exists between the incidence of these diseases. The research team used the CPCSSN database: a pan-Canadian collection of de-identified primary care electronic medical records from nearly 2 million patients that have been made available for research and surveillance. The webinar will present this method and discuss its advantages and limitations.

You may find the original International Journal of Population Data Science article here: [ Ссылка ]

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