Musculoskeletal disorders are the most common reason for sickness absence. Despite extensive research on return to work interventions the results are inconsistent and there is a lack of evidence in regards to who needs what measures. Furthermore, it is not only a question about who needs what; it is also a question about when. The aim of this project is to develop and evaluate an intelligent decision support system that i) enables early identification of individuals at risk of long-term sick leave due to musculoskeletal disorders, and ii) provides personalised recommendations to facilitate sustainable return to work. The SmaRTWork tool will utilize state-of-the-art artificial intelligence (AI) methodologies for the early risk prediction and subsequent tailoring of a personalised intervention to facilitate sustainable return to work. The core foundation for the decision support system will be case-based reasoning (CBR). The main principle of CBR is to reuse knowledge from previous successful cases to suggest solutions for new and similar cases. Workers who have been sick listed for 8 weeks due to musculoskeletal disorders will be invited to use The SmaRTWork tool. After consent they will receive credentials to access the web-based SmaRTWork tool which can be accessed by a computer/tablet/phone. The effect of the SmaRTWork tool will be evaluated in a randomized controlled trial. The main outcome will be time to sustainable return to work (i.e. one month back at work without relapse) based on registry data. There will be a process evaluation that will assess facilitators and barriers for implementation, and qualitative studies to explore how the sick-listed workers and other relevant stakeholders experience using the system.
Project leader: Lene Aasdahl
Institution: Institutt for samfunnsmedisin og sykepleie