Multimorbidity Health Analytics

Multimorbidity-related burden of disease

Multimorbidity can include almost any combination of variously severe conditions, show high variability in the trajectories of inpatient treatment (even within the same combinations of diseases, or disease clusters) and have a considerable impact on physical health, mental health, personal independence, quality of life, and physical disability. We apply data scientific methods such as machine learning, visual analytics and medical informatics to data that is accumulated during the delivery of healthcare for hospitalized patients in order to characterize the types and distribution of different disease clusters and to quantify these clusters in terms of care-related outcomes.

Project team: Patrick Beeler, Edouard Battegay, Marcus Cheetham, Saara Roininen, Karol Tarcak
Contact: Patrick Beeler