Elaine Dennison University of Reading; Royal Berkshire NHS Foundation Trust, Reading, UK
Citation: EMJ Rheumatol. 2026; https://doi.org/10.33590/emjrheumatol/AOM79MS8
What inspired the Rheumatology Academy and Collaborative Network (RheumACaN), and what unmet need were you hoping to address?
The inspiration came directly from patients, with many arriving in my clinic having already spent months with undiagnosed inflammatory arthritis, including axial spondyloarthritis (SpA). I had worked for over 16 years to improve the time to diagnosis. National audit data confirmed this was systemic, with only half of patients being referred within 3 working days, and fewer than 60% starting disease-modifying antirheumatic drugs (DMARD) within 6 weeks of referral. Primary care clinicians were seeing early inflammatory arthritis and not recognising it because it presents heterogeneously and features rarely in postgraduate education. RheumACaN was designed to close that gap systematically, combining education with pathway redesign rather than treating them as separate problems.
What were the most important findings, and how could they influence routine practice?
The mean clinician confidence in recognising and referring early inflammatory arthritis nearly doubled, and over 95% of participants reported being likely to change their practice. Referrals within 3 working days improved from 52% to 70% and have been sustained at 68% consistently, above the national benchmark of 53%. DMARD initiation within 6 weeks reached 66% locally against 60% nationally. The lesson for practice is that pathway redesign without education produces temporary change. Embedding new knowledge within restructured referral systems produces sustained improvement, and that combination is replicable in any rheumatology service willing to invest in it.
What are the greatest barriers preventing earlier diagnosis today?
Three barriers dominate. The first is recognition, as inflammatory arthritis presents heterogeneously, and a general practitioner (GP) who sees it twice a year will miss the pattern that a rheumatologist sees daily. The second is confidence, as even when inflammatory arthritis is suspected, the clinical commitment required to make an urgent referral into an overstretched specialty is significant, and uncertainty leads to watchful waiting rather than action. The third is system design, as most GP practices lack a standardised inflammatory arthritis referral pathway, a validated triage tool, or direct access to rheumatology advice without a formal referral. Changing all three simultaneously is what RheumACaN is attempting to do, and the sustained improvement in referral rates suggests that the combination works.
Which areas of rheumatology care are most in need of transformation?
Three stand out. First, the treat-to-target implementation presented at the European Alliance of Associations for Rheumatology (EULAR) 2026 Congress showed that only 40% of SpA outpatient visits were conducted with a validated disease activity index documented. You cannot hit a target if you have not measured it. Second, the integration of mental health and pain psychology into routine care showed that one in six patients with SpA has nociplastic pain and nearly 70% have depression by 6 months, yet pain phenotyping is not standard in any inflammatory arthritis assessment. Third, equity of access, as the diagnostic and therapeutic advances are not reaching patients in deprived communities, minority ethnic groups, or geographically underserved areas at the same rate. Measuring and publishing equity performance data should be a focus of future research.
Which AI and digital health developments are most promising, and where should expectations remain realistic?
The developments I find most promising are those addressing real clinical bottlenecks. The ADMIRA deep learning MRI reader, achieving near-expert accuracy for early arthritis synovitis scoring, addresses a genuine capacity problem, including radiology backlogs, inter-reader variability, and lack of specialist expertise outside academic centres. Our own machine learning triage pipeline for early inflammatory arthritis, supported by UK Research and Innovation (UKRI) funding, sits in the same category: augmenting clinical judgement at the GP referral decision point, embedded in existing systems, and requiring no additional steps from the clinician. Where expectations should remain realistic is in large-scale predictive analytics. The distance between a published algorithm and a deployed clinical tool is orders of magnitude greater than the scientific literature suggests, and that gap has eroded credibility in the field before. While we celebrate science, we must simultaneously invest in validation infrastructure.
Which presentations or themes stood out as having the greatest potential to influence near-term clinical practice?
Three stand out beyond the headline BE BOLD and FASTLANE results. The psoriatic arthritis (PsA) interception data showing that IL-23 inhibitors reduce PsA development risk by 84% versus TNF inhibitors over 17 years is relevant to joint dermatology-rheumatology decision-making for patients with psoriasis with musculoskeletal symptoms. The JAK-SPARE baricitinib data in polymyalgia rheumatica, with 65% glucocorticoid-free remission versus 17% on standard steroid taper, could transform long-term outcomes for one of the most common inflammatory conditions in older adults, reducing the cumulative steroid burden that drives so much preventable iatrogenic harm. The RheumACaN and CARE tool early referral data also stood out, not because of scientific novelty, but because they demonstrate that simple, implementable interventions can measurably improve care quality at the earliest and most critical point in the patient journey.
What research priorities should shape the future of inflammatory arthritis care over the next decade?
Four priorities feel most urgent. First is precision medicine at the tissue level, moving synovial pathotype-guided treatment from proof of concept to validated clinical practice in refractory inflammatory arthritis. Second is structural prevention in early disease, using formal randomised trials with imaging endpoints to test whether treating axial SpA and PsA within the first year of diagnosis permanently reduces irreversible structural damage. Third is the biology and treatment of persistent symptoms despite remission: nociplastic pain, fatigue, and sleep disturbance require dedicated mechanistic and intervention research programmes, not just the assumption that better inflammation control will resolve them. Lastly, AI implementation science moving validated algorithms through regulatory approval and real-world deployment should have equity built into the design from the outset, not addressed retrospectively.
If you could see one major change in rheumatology practice emerge from EULAR 2026, what would it be?
A 2-week referral standard for suspected inflammatory arthritis, equivalent to the 2-week wait that transformed cancer diagnosis in the UK. Not within 3 months on a generic musculoskeletal list; within 2 weeks, using a validated triage tool at the point of referral, with a structured early inflammatory arthritis pathway receiving the patient at the other end and a DMARD prescription within 6 weeks if the diagnosis is confirmed.
This requires no new drugs and no new technology. It requires investment in education, system redesign, and political will. Everything we celebrated at EULAR 2026, the head-to-head biologic trials, the molecular imaging, the AI tools, and precision medicine, all of it depends on the patient arriving in time for it to matter. The drugs we have are extraordinary. The pathways delivering patients to those drugs are not. That is the single change I want to see come out of EULAR 2026.
