DOI: 10.1093/bjd/ljag086.131 ISSN: 0007-0963

P104 Optimizing dupilumab initiation through standardized prescreening: a quality improvement project

Emma Mackender, Ilia Anna Petrou, Mahmud Ali

Abstract

Dupilumab is a biologic therapy for moderate-to-severe atopic dermatitis and eczema, which requires prescreening, patient education and timely treatment initiation. Variability in pretreatment tests and counselling can compromise patient safety and delay therapy. This audit aimed to improve the prescreening process that aligns with the BAD dupilumab guidance, to improve patient education and to reduce the time from treatment request to initiation. A quality improvement project was conducted using iterative ‘plan–do–study–act’ cycles. Initial ­retrospective data were collected on prescreening tests performed, patient counselling on side effects and vaccinations, and time from treatment request to initiation. Cycle 1 assessed baseline performance. Standardized online prescreening and monitoring checklists were then developed in line with BAD dupilumab guidance and were implemented across our service. Cycle 2 evaluated outcomes after implementation of the new checklists. Cycle 1 demonstrated gaps in care: 50% of patients had incorrect blood work, only 25% received vaccination counselling, and the mean treatment initiation time was 63.4 days. Following checklist implementation, cycle 2 found that compliance reached 100% for prescreening tests, side-effect counselling and distribution of patient information leaflets. The mean initiation time decreased to 45.6 days, a 28% reduction. While clinical quality targets were met, the reduction in time to treatment was not statistically significant. The standardized checklist improved the prescreening parameters and patient education. Remaining delays are due to systemic and administrative factors, informing the focus of the future cycle. This project demonstrates the effectiveness of iterative quality improvement in enhancing delivery of biologic therapy and highlights opportunities for further optimization.

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