Multimorbidity Management

***

Quantification of therapeutic conflict in multimorbid patients

Multimorbidity refers to the presence of multiple concurrent acute or chronic diseases in one person. Clinical decision-making for multimorbid patients can be challenging. Therapeutic conflict can occur when the treatment for one medical condition is contraindicated by potentially harmful interactions with one or more of the patient’s other conditions or medications (i.e., drug-drug and drug-disease interactions). This project focuses on developing and testing assessment and visualization tools that can aid the clinical decision maker in the process of identifying complex combinations of potentially harmful interactions, highlighting critical areas of patient burden, and prioritizing treatment options.

Project status: ongoing
Contact: Prof. Dr. Edouard Battegay and Dr. Marcus Cheetham

***

Multimorbidity-specific burden of disease

Multimorbid cases can have almost any combination of variously severe conditions, show high variability in the course of treatment (even within the same combination of conditions), and vary considerably in terms of physical and mental health, personal independence, quality of life, and physical disability. The aim of this project is to characterize the types and distribution of different combinations of conditions and to examine these in terms of treatment-related outcomes. To this end, we apply data scientific methods, such as machine learning and visual analytics, to healthcare data accumulated during healthcare delivery of hospitalized patients.

Project status: ongoing
Contact: Dr. Patrick Beeler and Dr. Marcus Cheetham

***
Identification of markers of disease burden in multimorbidity

The effects of multiple chronic diseases within a person may manifest as changes in the structure and function of the brain. The main research objective of this project is to apply knowledge discovery techniques in patient samples of EEG-based brain imaging data in order to identify reliable neural markers of disease burden in multimorbid patients. These markers may provide new ways for describing and predicting effects of multimorbidity.

Project status: ongoing
Contact: Dr. Seyed Valizadeh and Dr. Marcus Cheetham