Elena Tseli

Research problem Chronic pain is a leading cause of disability worldwide with huge impact on public health and welfare systems. Interdisciplinary treatment (IDT) is currently the established treatment in Swedish specialist care, but recent research shows that treatment effects are small or non-existent. It is recognised that both selection processes and individualised treatment need improvement! With the purpose to enhance the effectiveness of Swedish specialised IDT in patients with chronic pain we plan for three Objectives:To develop an intelligent Clinical Decision Support System for use in treatment individualisation of specialised IDT and validate its design, performance, and feasibility.To prospectively evaluate the system’s clinical effectiveness and cost-utility in a registry-based clustered-randomised control trial (RRCT).To implement the support system in Swedish specialised IDT. The system will facilitate patient selection and guide context-specific individualised treatment strategies by systematically learning patient-specific patterns from big-data. Data and methodWe will apply artificial intelligence (AI) methods to clinical data from over 60,000 patients with chronic pain across 40 specialist units in Sweden for the period 2009-2022 (the FRIDA-database). FRIDA is today one of the world´s largest rehabilitation databases that synchronises unique and longitudinal data from the National Register of Pain Rehabilitation with four other national registers. The project will be carried out in close collaboration with healthcare providers, patient organisations, policymakers and the business community. Plan for project realisationOur multi-professional research team has all the necessary expertise to successfully complete each project stage, from system development to evaluation of effectiveness and cost utility, and implementation. The timeframe of this Forte application includes Objective 1 and the major part of the RRCT. RelevanceA decision support system that can now be developed in FRIDA has great potential to streamline Swedish multimodal specialist care

AI methods in combination with “big-data” are recommended in precision medicine to optimize treatment. This AI support system can significantly improve health-related quality of life, reduce emotional suffering and sick leave for patients with chronic pain and be of great socio-economic value to society.