The Minimum Data Set for Rare Diseases: Systematic Review.

Area of Science:

• Health Informatics
• Rare Disease Research
• Data Standardization

Background:

• Minimum Data Sets (MDS) are crucial for health surveillance and research, but complexity in rare disease (RD) data hinders indicator generation.
• Existing literature reveals global challenges in collecting, recording, and structuring RD data.
• Standardized MDS are essential for effective health surveillance and generating population indicators.

Approach:

• A systematic review methodology, guided by Joanna Briggs Institute principles and PRISMA guidelines, was employed.
• Four databases were searched, and data elements were extracted and categorized using WHO digital health guidelines.
• Quality assessment was performed using the STROBE checklist.

Key Points:

• A review of 20 studies found a lack of terminological standardization and consistent structure in MDS for RDs.
• Included studies often had limited scope, focusing on specific RDs or contexts.
• Data science and clinical expertise were used to develop a fundamental global MDS for RD patient records.

Conclusions:

• Standardizing and categorizing RD MDS findings is challenging due to varied study structures.
• A fundamental global MDS for RDs has been designed, addressing clinical and management data needs.
• This MDS can inform public policy and strategic decision-making for rare diseases.