Developing Digital Healthcare Interventions using Case-Based Reasoning

CBR has a long tradition in medical applications. While most applications focus on the recommendation and decision support for clinicians in specialized care, the selfBACK project has created an app for low back pain patients based on CBR to create self-management plans and automatically follow up on their progress. This talk presents the selfBACK approach that delivers customized healthcare and lifestyle recommendations in a primary care setting to supplement traditional care. We show how we build the CBR system with an interdisciplinary team and which lessons we learned on basing our work on CBR. The effectiveness of the final application has been evaluated in a randomized controlled trial in which a total of 461 patients participated. All participants were randomized to receive self-management support in addition to usual care (selfBACK) or usual care alone. Further, we will discuss the challenges and opportunities of using CBR as a methodology when building novel applications in interdisciplinary teams. In the end, we will give an outlook towards recently started projects in which we build upon the work from the selfBACK project aiming to support primary care clinicians in treatment planning or facilitating journeys of patients with musculoskeletal disorders returning to work.