Community Research and Development Information Service - CORDIS

H2020

selfBACK Report Summary

Project ID: 689043
Funded under: H2020-EU.3.1.

Periodic Reporting for period 1 - selfBACK (A decision support system for self-management of low back pain)

Reporting period: 2016-01-01 to 2016-12-31

Summary of the context and overall objectives of the project

The recent global burden of disease study showed that low back pain (LBP) is the most significant contributor to disability in Europe. Most patients seen in primary care with LBP have non-specific LBP (≥85%), i.e., pain that cannot reliably be attributed to a specific disease or pathology. LBP is the fourth most common diagnosis seen in primary care (after upper respiratory infection, hypertension, and coughing). Self-management in the form of physical activity and exercise programs constitutes the core component in the management of non-specific LBP; however, adherence to a self-management plan is challenging due to lack of feedback and reinforcement. During this project, we will develop a decision support system - SELFBACK - that will be used by the patient him/herself to facilitate, improve and reinforce self-management of LBP. Specifically, SELFBACK will be designed to assist the patient in deciding and reinforcing the appropriate actions to manage own LBP after consulting a health care professional in primary care. The decision support is conveyed to the patient via a smartphone app in the form of advice for self-management. The advice is tailored to each patient based on the symptom state, symptom progression, the patients goal-setting, and a range of patient characteristics including information from a physical activity-detecting wristband worn by the patient. The second part of the project is evaluating the effectiveness of SELFBACK in an international multi-centre randomized controlled trial (RCT) using pain-related disability as primary outcome. The RCT targets care-seeking patients in primary care with non-specific LBP as their main health problem. We envisage that patients who use SELFBACK will have 20% reduction in pain-related disability at 9 months follow-up compared to patients who receive treatment-as-usual. Process evaluation will be carried out as an integrated part of the trial to document the implementation and map the patients’ satisfaction with SELFBACK. A business plan with a targeted commercialization strategy is being developed to transfer the SELFBACK technology into the market.

Work performed from the beginning of the project to the end of the period covered by the report and main results achieved so far

The first milestone of the project – completion of the design phase of the SELFBACK app – was set and achieved in month 6. This milestone included a literature review, collecting relevant data from external resources, and the user interface design. Moreover, the project infrastructure has been set up and the first version of the data management plan is completed. In the reporting period, the beneficiaries started working towards the second milestone that is due in month 18. For this milestone the basic integration infrastructure is in place and the first completed components are available, including a model for physical activity recognition, a feature extraction algorithm, similarity measures as part of the case-based reasoning system, specification for the mobile app, demonstration of the web-based questionnaire.

Progress beyond the state of the art and expected potential impact (including the socio-economic impact and the wider societal implications of the project so far)

The SELFBACK project targets the most common musculoskeletal disorder and the most significant contributor to disability in Europe. In the RCT, we envisage that patients who use SELFBACK will have 20% reduction in pain-related disability at 9 months’ follow-up compared to patients receiving treatment as usual. To achieve this, the SELFBACK system will be developed and designed to improve the participation of the patient in the care process, thereby enhancing motivation and the perception of ‘usefulness’ by the patient. The self-management plan will be tailored to each patient by integrating case-based reasoning and a machine-learning component into the SELFBACK system. Case-based reasoning is a technology that uses information about successful past cases of similar patients to optimize advice for self-management for new patients. The use of case-based reasoning and machine learning will enable us to develop predictive models that can be used to tailor self-management plans for each individual patient. By providing tailored feedback, decision support and improved understanding of own LBP, SELFBACK will empower the patient to improve self-management and thereby reduce the risk of long-term disability. With SELFBACK, the patient will be equipped with a tool that is far beyond the state-of-the-art to facilitate, improve and reinforce self-management of non-specific LBP. Although the effectiveness of SELFBACK remains to be proven, the potential cost-benefit is without doubt substantial. We estimate that the total cost of using SELFBACK will range between 120-150 EUR per patient, including the app, the activity-detecting wristband, and brief education to enable safe use of SELFBACK. SELFBACK does not require direct medical supervision and can easily be made available for a large number of people, thereby resulting in a highly cost-effective use of resources.

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