Perceptions of healthcare professionals in rheumatology on the use of prediction models in clinical practice

Abstract

OBJECTIVES: Prediction models are increasingly developed to aid decision-making in RA, but none are currently included in guidelines. The aim of this study was to explore rheumatology healthcare professionals' perceptions of using prediction models in everyday clinical practice. METHODS: An exploratory qualitative study was conducted using semi-structured interviews with rheumatologists and nurse practitioners involved in RA care in the Netherlands. Participants were purposively sampled based on work experience, academic degree, profession and care setting. Interviews were transcribed and analysed thematically following Braun and Clarke's framework. RESULTS: Fifteen interviews uncovered for overarching themes. First, building support for prediction models depended on trust, awareness, understanding of model inputs and limitations, perceived clinical usefulness, evidence and cost-effectiveness. Second, making prediction models workable in routine care required integration into electronic health records, minimal additional workload, reliance on routinely collected data and actionable outputs. Third, healthcare professionals (HCPs) positioned prediction models within clinical judgement and patient care: models were considered valuable when supporting, rather than replacing, professional judgement and shared decision-making, while helping to communicate uncertainty and clarify difficult decisions. Fourth, HCPs anticipated consequences for care organization, medication use, professional autonomy and personalized care, including concerns about misuse by external parties, compulsion and unintended workload or loss of patient visibility. CONCLUSION: Rheumatology healthcare professionals value prediction models, but only if they are interpretable, clearly beneficial, integrated into workflows and protect professional autonomy. Addressing these concerns is essential for turning models into useful clinical decision tools.