E012 How clinicians perceive and use electronic patient-reported outcome measures in rheumatology: barriers and predictive potential

Abstract Background/Aims Use of electronic patient-reported outcome measures (ePROMs) in routine rheumatology practice has increased in recent years but remains far from universal. Barriers persist at patient, clinician, and organisational levels, and there is limited formal analysis of how ePROMs are used. This makes it difficult to assess their potential and scope in practice. With digital tools now widespread, it is conceivable that ePROM data could be used to generate predictions on patient outcomes; however, clinician perceptions of this are unknown. This project aimed to assess current ePROM usage, perceived barriers to implementation, and clinician attitudes toward their potential use in supporting clinical decision making. We aimed to: determine the extent of ePROM use in routine rheumatology practice and by which members of the multidisciplinary team; explore clinician perceptions of ePROM usefulness and barriers to their use; assess whether clinicians would feel comfortable making clinical decisions assisted by predictions of patient outcomes derived from ePROM data; identify what level of predictive accuracy clinicians would require to trust such tools, and whether this varies by decision type. Methods A 17-item qualitative questionnaire was distributed via the British Society for Rheumatology, European Digital Rheumatology networks, and NHS trusts locally, using Microsoft Forms. Responses were collected electronically and analysed qualitatively. Results Twenty-eight responses were received from a range of MDT members with varying clinical experience. Slightly over half reported regular ePROM use. Most respondents viewed ePROMs as valuable in practice, though opinions were bimodally distributed with no neutral responses. Reported barriers centred mainly on clinician and organisational issues rather than patient factors. Most participants felt outcome predictions generated from ePROM data would be useful; just over 50% said they would be confident to omit an in-person review if a prediction indicated disease remission. Seventeen of 28 respondents would accept a 20% margin of error for such a decision, while 14 of 28 would only alter medications if predictions were within a 10% margin of error. Conclusion A slim majority of clinicians currently use ePROMs, and most view them as valuable. None expressed indifference toward their utility. Most would welcome predictive modelling using ePROM data to inform decisions, though required accuracy thresholds vary by clinical context - greater precision being expected for medication changes than for decisions such as timing of follow-up. Disclosure E. Parikh: None. P. Hamann: Royalties; I have a limited royalty agreement with Living With Ltd Software Company for the development of the smartphone application -Living With Rheumatoid Arthritis. Honoraria; In the past three years have also received honoraria from Gilead and AbbVie Pharmaceuticals for the production of training materials on remote monitoring for patients with arthritis.