Midland Regional Hospital, Tullamore

Abstract Background/Aims: Background Axial Spondyloarthritis (AxSpA) is a chronic inflammatory rheumatic disease affecting the axial skeleton that can cause both extra musculoskeletal (EMMs) and extra articular manifestations (EAMs) (Wright et al 2020). Nurse-led care (NLC) has demonstrated non-inferiority to consultant-led care in Rheumatoid Arthritis patient cohorts for over a decade (Ndosi et al, 2014, Lopatina et al, 2021), with a paucity of data in comparable inflammatory diseases. Treatment with non-steroidal anti-inflammatory drugs (NSAIDs), physiotherapy, and biologic medications have been the standard of care. While ASAS guidelines recommend multidisciplinary care, nursing input is not specifically referred to in this guidance (Ramiro et al, 2023), however the EULAR recommendations for role of the nurse in management of chronic inflammatory arthritis advocates for shared decision making between nurse and patient, and timely access to nursing care (Bech et al, 2020). Aim To demonstrate efficacy of NLC for AxSpA patients through year 1 post diagnosis; by demonstrating reduction in patient reported outcome measures/ NSAID use and maximising treatment persistence. Methods Following confirmation of AxSpA diagnosis, patients were referred to join the NLC pathway. Across 3/4 appointments, outcome measures were collected and patients received education about their diagnosis and management plan, trial of minimum 1 NSAID and/or biologic initiation/ switch where appropriate, EMMs/ EAMs assessment, comorbidity screening, lifestyle (including family planning) and vaccine advice to reduce infection risk and medication reconciliation. Patients were referred for physiotherapy at their closest centre to home as per Slaintecare recommendations, and if appropriate were encouraged to stop smoking. Results From January-December 2024, 60 patients enrolled with an average age at diagnosis of 38 years. 60% (36) of patients were male, and of the sixty patients, 77% (46) attended minimum 3 visits. NSAID use reduced from 50% regular use at visit 1 to 68% rare use by visit 3. Biologic use was maintained at 80% across visit 2 and 3, with 70% (42) same biologic persistence achieved. 53% (32) confirmed physiotherapy review by visit 2. Average outcome measures at each visit are as follows; Visit 1 BASDAI 4.53, BASFI 3.71, BAS-G 5.41, BASMI 2.92; Visit 2 BASDAI 3.55, BASFI 2.72, BAS-G 4.26, BASMI 2.55; and Visit 3 BASDAI 3.50, BASFI 2.80, BAS-G 3.57, BASMI 2.30. Further analysis is ongoing. Conclusion NLC has been shown to have a positive impact on a number of relevant patient outcomes in this cohort. Challenges included maintaining dedicated clinic time which is essential to meeting review deadlines, and changes have been made locally while data collection is ongoing. While further research is needed to confirm non-inferiority to consultant-led care, we propose that AxSpA patients are a suitable cohort for NLC. Disclosure E. Shinners: Honoraria; ES has received honaria from Roche, Pfizer, Johnson & Johnson. Grants/research support; ES has received unrestricted educational grant from Johnson & Johnson. A. Gorman: None.

Introduction Robotic ventral hernia repair is increasing worldwide. Few robotic ventral hernia simulation models are commercially available. There is a need for high-fidelity simulation models within this domain. We aimed to evaluate the validity of a IMRA Surgical hydrogel model currently in use as part of the national postgraduate residency training programme in Ireland. Methods A mixed-methods study was performed. Twenty participants drawn from a convenience sample were randomly assigned to perform a robotic transabdominal preperitoneal ventral hernia repair on a minimum of two robotic platforms: Versius™ (CMR Surgical, United Kingdom), Hugo™ robotic-assisted surgery (RAS) system (Medtronic, Dublin, Ireland), and Da Vinci X/Xi™ (Intuitive, Sunnyvale, CA, USA). Recorded procedures were assessed quantitatively for performance independently by a minimum of three blinded expert assessors using GEARS and RACE scores. Participant views and examiner responses were gathered from subjective feedback. Analysis and validity evidence were interpreted using Messick’s Framework. Results Twenty participants completed forty-six robotic ventral hernia repairs using the IMRA Surgical simulated hydrogel model. Most experts (75%) agreed that the model appropriately simulated realistic human anatomy and tissue handling. Each procedural micro-component (and defined psychomotor skill) was described by participants as being more realistic using the hydrogel models compared to other simulation models they had used. GEARS (early resident 16 vs senior resident 16.71 vs attending 18.5, p-value 0.0051) and RACE scores (early resident 18.75 vs senior resident 19.92 vs attending 21.67, p-value 0.0078) were persistently higher and proportionate to the grade of individual operative experience. Conclusion We have shown that IMRA Surgical hydrogel ventral hernia models have collated substantial validity evidence, including face, content and construct validity. Whether the skills acquired on this model can translate into improved in-vivo operative performance remains to be elucidated.

Artificial Intelligence (AI) driven documentation systems are positioned to enhance documentation efficiency and reduce documentation burden in the healthcare setting. The administrative burden associated with clinical documentation has been identified as a major contributor to health care professional (HCP) burnout. The current systematic review aims to evaluate the efficiency, quality, and stakeholder opinion regarding the use of AI-driven documentation systems. Using the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines a comprehensive search was conducted across PubMed, Embase and Cochrane library. Two independent reviewers applied inclusion and exclusion criteria to identify eligible studies. Details of AI technology, document type, document quality and stakeholder experience were extracted. The review included 11 studies. All included studies utilised Chat generated pretrained transformer (Chat GPT, Open AI, CA, USA) or an ambient AI technology. Both forms of AI demonstrated significant potential to improve documentation efficiency. Despite efficiency gains, the quality of AI-generated documentation varied across studies. The heterogeneity of methods utilised to assess document quality influenced interpretation of results. HCP opinion was generally positive, users highlighted ease of use and reduced task load as primary benefits. However, HCPs also expressed concerns about the reliability and validity of AI-generated documentation. Chat GPT and ambient AI show promise in enhancing the efficiency and quality of clinical documentation. While the efficiency benefits are clear, the challenges associated with accuracy and consistency need to be addressed. HCP experiences indicate a cautious optimism towards AI integration, however reliability will depend on continued refinement and validation of the technology.