Multidisciplinary data infrastructures in multiple sclerosis: Why they are needed and can be done!

Area of Science:

• Neurology
• Rehabilitation Medicine
• Biomedical Informatics

Background:

• Personalized treatment is a key goal in multiple sclerosis (MS) management.
• Current approaches may not fully capture the complexity of MS.
• A holistic view is needed to optimize patient care.

Purpose of the Study:

• To advocate for multidisciplinary measurements in multiple sclerosis (MS) care.
• To highlight the importance of combining clinical, functional, and patient-reported outcomes.
• To emphasize the role of extensive patient profiling in enhancing personalized treatment and rehabilitation.

Main Methods:

• Review of current multidisciplinary data initiatives in MS.
• Elaboration on four key reasons supporting a multidisciplinary approach.
• Discussion of interdependent factors in MS progression and treatment.

Main Results:

• MS disease activity and progression are complex and multidimensional.
• Functioning, progression, treatment, and rehabilitation effects are interconnected.
• Personalized healthcare relies on system biology dynamics and patient-specific data.

Conclusions:

• Multidisciplinary data collection, including patient-reported outcomes, is crucial for personalized MS treatment and rehabilitation.
• Integrating diverse data types enhances understanding and management of MS.
• Further investment in longitudinal, multidisciplinary data is recommended for the MS community.