Table Info

Table 1.

Differences between structured databases and unstructured information in the research of RA

Characteristic	Structured databases	Unstructured information
Definition	Uses diagnostic codes and predefined formats	Found in free text or images
Data source	Claims; prescriptions and administrative databases	Clinical notes; imaging data
Data collection	International Classification of Diseases, 9th edition (ICD-9), ICD-10 codes	Natural language processing (NLP) for text; convolutional neural network (CNN) for imaging
Examples of RA research	Detailed study of comorbidities; treatment safety	Identification of RA patients; extraction of outcome measures
Limitations	Limited by predefined formats; requires systematic coding; possible missing variables and biases	Analytical challenges; require precision in data detection; design challenges in algorithms
Benefits	Systematic and standardized data; detection of long-term trends; prevalence in broad populations	Enhances collection of specific features; contributes to multimodal research

Declarations

Acknowledgments

The authors thank the Spanish Foundation of Rheumatology for providing medical editorial assistance during the preparation of the manuscript.

Author contributions

DB: Conceptualization, Writing—original draft, Writing—review & editing. CPR: Conceptualization, Writing—review & editing, Validation. Both authors read and approved the submitted version.

Conflicts of interest

DB reports speakers bureau/grants from AbbVie, Lilly, MSD, Pfizer, UCB, and Novartis outside of the submitted work. He is a part-time worker at Savanamed. CPR reports speakers bureau/grants from Abbvie, Pfizer, Novartis, Lilly, and Roche outside of the submitted work.

Ethical approval

Not applicable.

Consent to participate

Not applicable.

Consent to publication

Not applicable.

Availability of data and materials

Not applicable.

Funding

Not applicable.

Copyright

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