Person-Centred AI Support in Interdisciplinary Rehabilitation for Chronic Pain

This cluster randomized controlled trial evaluates whether a person-centred, AI-supported Clinical Decision Support System (CDSS) can improve outcomes and cost-effectiveness in interdisciplinary rehabilitation for people with complex chronic pain. The CDSS is designed to assist clinicians in making personalized treatment decisions within standard interdisciplinary treatment (IDT). It has been developed using machine learning models trained on real-world data from over 100,000 patients in the Swedish Quality Registry for Pain Rehabilitation (SQRP), linked to several national registers, including the National Patient Register, the Prescribed Drug Register, the Social Insurance Agency database (MiDAS), and the Cause of Death Register. This enables individualized predictions of treatment outcomes, work ability, and healthcare utilization.

The trial includes 400 adult patients with chronic pain, enrolled at 20 IDT clinics randomized to either CDSS-supported or standard IDT. The study has three phases: feasibility, effectiveness, and implementation. The primary outcome is a patient-prioritized composite single-index of health-related well-being, based on domains such as pain, sleep, physical and mental health, emotional distress, and work ability. Patients prioritize these domains together with their clinical team, enabling a person-centred assessment. Secondary outcomes include HRQoL (EQ-5D, SF-36), emotional distress (HADS), and work ability (WAI), measured at baseline, post-treatment, 6- and 12-month follow-up.

A parallel mixed-methods process evaluation will examine implementation outcomes such as usability, clinician adherence, and workflow integration, using logs, surveys (e.g., S-NoMAD), and interviews. Normalization Process Theory guides the analysis. Cost-utility will be assessed using QALYs and ICERs from a societal perspective, with long-term projections using simulation models. Results will be reported in peer-reviewed publications.