Rheumatoid arthritis patients' perspective on the use of prediction models in clinical decision-making

Area of Science:

• Rheumatology
• Medical Informatics
• Health Services Research

Background:

• Numerous prediction models are being developed to enhance rheumatoid arthritis (RA) diagnosis and treatment.
• Clinical implementation of these RA prediction models remains limited.

Purpose of the Study:

• To explore factors influencing the acceptance of prediction models in clinical decision-making among RA patients.
• To understand patient perspectives on the role and impact of prediction models in their care.

Main Methods:

• Qualitative study design utilizing thematic analysis of semi-structured interviews.
• Purposive sampling to ensure a comprehensive overview of influencing factors.
• Interview topics informed by pilot data.

Main Results:

• Patients generally expressed positivity towards using prediction models in clinical decision-making.
• Six key themes emerged: need for information, trust factors, supportive role of models, personal benefits, willingness to contribute data, and impact on caregiver relationships.
• Data saturation was achieved after 12 interviews.

Conclusions:

• RA patients show general acceptance of prediction models for treatment, provided specific conditions and concerns are met.
• Findings can guide the development and implementation of RA prediction models to improve patient acceptability.
• Addressing patient needs for information and trust is crucial for successful integration.