ESTRO 2025 - Abstract Book

S2265

Interdisciplinary – Health economics & health services research

ESTRO 2025

Material/Methods: A mobile application, Accompain, was designed for monitoring pain, rescue medication and other symptoms. Recruitment time was 24 months including adult patients with oncologic pain. Results: From August 2022 to October 2024, 64 patients used Accompain. The median age was 62 years (33-94). 20 male and 44 female. 31 patients with metastatic stage and 33 without metastases (primary tumors: rectal cancer, breast cancer and others). There were 1712 records with a mean of 53.00 (± 71.43) days of follow-up. Each patient recorded a mean of 46.37 (± 68.12) questionnaires. The levels of VAS (visual analogic scale), pain interference on general activity, pain interference on mood, and pain interference on sleep status based on EORTC QLQ C30 were analyzed at 15 days, one month and more than one month after radiotherapy treatment. VAS was 5.57 (±1.80), 5.12 (±2.47), 3.87 (±2.53) and 3.31 (±1.62) respectively; interference with general activity of 7.00, 5.46 (±3.15) and 6.13 (±2. 57) respectively; interference with mood was 4.00, 5.00 (±3.53) and 5.63 (±2.83) respectively; and interference with ground state was 8.00, 5.38 (±3.39) and 6.63 (±3.28) respectively. The most frequent symptom was fatigue. A total of 240 alerts were generated to the physicians' professional mail of 34 patients: 94 for VAS > 8; 108 for VAS increase of 30%; and 38 alerts for more than 5 rescues per day. Telematic consultations were performed for each alert. No patient required hospital admission or invasive procedures for pain control. Conclusion: Home monitoring emerges as an effective strategy for pain control in cancer patients. Accompain has made it possible to know the clinical situation of patients at home, anticipating the adjustment of treatments and impacting not only on the quality of care, but also on better management by the medical professional. Digital Poster Integration of Artificial Intelligence in Radiation Oncology in Ireland: Challenges and Recommendations Ciaran Malone 1 , Aisling Barry 2 , Fiona Bonas 3 , Aileen Flavin 4 , Paul Hill 2 , Claire Keating 2 , Imelda Kelly 5 , Deirdre Love 6 , Ciara Lyons 7 , Orla McArdle 8 , Eve O'Toole 6 , Evelyn O'Shea 9 , Brendan McClean 1,10 1 Department of Radiation Oncology, St.Luke's Radiation Oncology Network, Dublin, Ireland. 2 Department of Radiation Oncology, CUH, Cork, Ireland. 3 Assistant National Director, NCCP, Dublin, Ireland. 4 Department of Radiation Oncology, UMPC, Cork, Ireland. 5 Secretary to ROWG, NCCP, Dublin, Ireland. 6 Evidence and Quality Hub, NCCP, Dublin, Ireland. 7 Department of Radiation Oncology, UMPC, Waterford, Ireland. 8 Department of Radiation Oncology, SLRON, St.Luke's Hospital, Dublin, Ireland. 9 Programme Manager, NCCP, Dublin, Ireland. 10 Department of Physics, UCD, Dublin, Ireland Purpose/Objective: The adoption of Artificial Intelligence (AI) in healthcare is advancing rapidly, offering transformative potential for improved patient care. In radiation oncology, the integration of AI holds significant promise. However, fully realising the benefits of AI in Radiation Oncology is both challenging and complex, demanding a flexible, multidisciplinary approach capable of responding to the rapidly changing landscape of AI solutions. To address these challenges, a National Expert Working Group (NEWG) was established in Ireland, tasked with reviewing the current landscape of AI in Radiation Oncology, identifying key challenges, and developing recommendations for its successful integration in Ireland. Keywords: telemedicine, pain cancer 606