Data Resource Profile: The Multiple Sclerosis Documentation System 3D and AOK PLUS Linked Database (MSDS-AOK PLUS).

Area of Science:

• Neurology
• Health Informatics
• Epidemiology

Background:

• Real-world evidence (RWE) in multiple sclerosis (MS) research is often fragmented due to limitations in data elements within disparate datasets.
• Existing datasets typically capture either administrative/claims data or detailed clinical information, hindering a holistic patient view.

Purpose of the Study:

• To introduce and describe the development of a novel, integrated database (MSDS-AOK PLUS) linking administrative claims with detailed clinical records for MS patients.
• To demonstrate the potential of this linked database for enhancing the quality and scope of MS-specific real-world studies.

Main Methods:

• A linked database, MSDS-AOK PLUS, was created by merging data from the AOK PLUS sickness fund (administrative claims, costs) and the Multiple Sclerosis Documentation System (MSDS3D) (clinical parameters, patient-reported outcomes).
• Patient data linkage was achieved by mapping insurance IDs to registry IDs, followed by anonymization.
• Informed consent was obtained from patients treated at the Center of Clinical Neuroscience (ZKN) and insured by AOK PLUS.

Main Results:

• The MSDS-AOK PLUS database integrates comprehensive patient diagnoses, treatment histories, healthcare resource utilization, and associated costs with detailed clinical functional performance and patient-reported outcomes.
• The database currently includes 500 patients and is actively expanding.
• A use case demonstrated the database's utility in characterizing patient profiles, treatment patterns, resource use, and costs.

Conclusions:

• The novel MSDS-AOK PLUS database overcomes data fragmentation challenges in MS research by linking administrative and clinical data sources.
• This integrated approach significantly enhances the depth and breadth of real-world data available for multiple sclerosis studies.
• The database provides a valuable resource for improving the quality and scope of real-world evidence generation in MS.