Design and Development of a Decision Support Package for Low Back Pain

BACKGROUND Low back pain (LBP) is a leading cause of disability worldwide. Most patients with LBP encountered in primary care settings have nonspecific LBP, that is, pain with an unknown pathoanatomical cause. Self-management in the form of physical activity and strength and flexibility exercises along with patient education constitute the core components of the management of nonspecific LBP. However, the adherence to a self-management program is challenging for most patients, especially without feedback and reinforcement. Here we outline a protocol for the design and implementation of a decision support system (DSS), selfBACK, to be used by patients themselves to promote self-management of LBP. OBJECTIVE The main objective of the selfBACK project is to improve self-management of nonspecific LBP to prevent chronicity, recurrence and pain-related disability. This is achieved by utilizing computer technology to develop personalized self-management plans based on individual patient data. METHODS The decision support is conveyed to patients via a mobile phone app in the form of advice for self-management. Case-based reasoning (CBR), a technology that utilizes knowledge about previous cases along with data about the current patient case, is used to tailor the advice to the current patient, enabling a patient-centered intervention based on what has and has not been successful in previous patient cases. The data source for the CBR system comprises initial patient data collected by a Web-based questionnaire, weekly patient reports (eg, symptom progression), and a physical activity-detecting wristband. The effectiveness of the selfBACK DSS will be evaluated in a multinational, randomized controlled trial (RCT), targeting care-seeking patients with nonspecific LBP. A process evaluation will be carried out as an integral part of the RCT to document the implementation and patient experiences with selfBACK. RESULTS The selfBACK project was launched in January 2016 and will run until the end of 2020. The final version of the selfBACK DSS will be completed in 2018. The RCT will commence in February 2019 with pain-related disability at 3 months as the primary outcome. The trial results will be reported according to the CONSORT statement and the extended CONSORT-EHEALTH checklist. Exploitation of the results will be ongoing throughout the project period based on a business plan developed by the selfBACK consortium. Tailored digital support has been proposed as a promising approach to improve self-management of chronic disease. However, tailoring self-management advice according to the needs, motivation, symptoms, and progress of individual patients is a challenging task. Here we outline a protocol for the design and implementation of a stand-alone DSS based on the CBR technology with the potential to improve self-management of nonspecific LBP. CONCLUSIONS The selfBACK project will provide learning regarding the implementation and effectiveness of an app-based DSS for patients with nonspecific LBP. REGISTERED REPORT IDENTIFIER RR1-10.2196/9379

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A digital decision support system (selfBACK) for improved self-management of low back pain: a pilot study with 6-week follow-up

Pilot and Feasibility Studies ◽

10.1186/s40814-020-00604-2 ◽

2020 ◽

Vol 6 (1) ◽

Author(s):

Louise Fleng Sandal ◽

Cecilie K. Øverås ◽

Anne Lovise Nordstoga ◽

Karen Wood ◽

Kerstin Bach ◽

...

Keyword(s):

Low Back Pain ◽

Back Pain ◽

Decision Support ◽

Pilot Study ◽

Decision Support System ◽

Support System ◽

Self Management ◽

Low Back

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Effect of two behavioural ‘nudging’ interventions on management decisions for low back pain: a randomised vignette-based study in general practitioners

BMJ Quality & Safety ◽

10.1136/bmjqs-2018-008659 ◽

2018 ◽

Vol 28 (7) ◽

pp. 547-555 ◽

Cited By ~ 2

Author(s):

Jason Soon ◽

Adrian C Traeger ◽

Adam G. Elshaug ◽

Erin Cvejic ◽

Chris G Maher ◽

...

Keyword(s):

Low Back Pain ◽

Back Pain ◽

Decision Support ◽

Clinical Decision Support ◽

Clinical Decision ◽

Value Management ◽

Low Back ◽

Management Decisions ◽

Default Option ◽

Clinical Vignettes

Objective‘Nudges’ are subtle cognitive cues thought to influence behaviour. We investigated whether embedding nudges in a general practitioner (GP) clinical decision support display can reduce low-value management decisions .MethodsAustralian GPs completed four clinical vignettes of patients with low back pain. Participants chose from three guideline-concordant and three guideline-discordant (low-value) management options for each vignette, on a computer screen. A 2×2 factorial design randomised participants to two possible nudge interventions: ‘partition display’ nudge (low-value options presented horizontally, high-value options listed vertically) or ‘default option’ nudge (high-value options presented as the default, low-value options presented only after clicking for more). The primary outcome was the proportion of scenarios where practitioners chose at least one of the low-value care options.Results120 GPs (72% male, 28% female) completed the trial (n=480 vignettes). Participants using a conventional menu display without nudges chose at least one low-value care option in 42% of scenarios. Participants exposed to the default option nudge were 44% less likely to choose at least one low-value care option (OR 0.56, 95%CI 0.37 to 0.85; p=0.006) compared with those not exposed. The partition display nudge had no effect on choice of low-value care (OR 1.08, 95%CI 0.72 to 1.64; p=0.7). There was no interaction between the nudges (OR 0.94, 95% CI 0.41 to 2.15; p=0.89).InterpretationA default option nudge reduced the odds of choosing low-value options for low back pain in clinical vignettes. Embedding high value options as defaults in clinical decision support tools could improve quality of care. More research is needed into how nudges impact clinical decision-making in different contexts.

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