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Cost-effectiveness of using a motion-sensor biofeedback treatment approach for the management of sub-acute or chronic low back pain: economic evaluation alongside a randomised trial

Overview of attention for article published in BMC Musculoskeletal Disorders, January 2017
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Title
Cost-effectiveness of using a motion-sensor biofeedback treatment approach for the management of sub-acute or chronic low back pain: economic evaluation alongside a randomised trial
Published in
BMC Musculoskeletal Disorders, January 2017
DOI 10.1186/s12891-016-1371-6
Pubmed ID
Authors

Terry Haines, Kelly-Ann Bowles

Abstract

Low back pain is a common and costly condition internationally. There is high need to identify effective and economically efficient means for managing this problem. This study aimed to explore the cost-effectiveness of a novel motion-sensor biofeedback treatment approach in addition to guidelines-based care compared to guidelines-based care alone, from a societal perspective over a 12 month time horizon. This was an incremental cost-effectiveness analysis conducted concurrently with a pilot, cluster randomized controlled trial. Health care resource use was collected using daily diaries and patient-self report at 3, 6 and 12 month follow-up assessments. Productivity was measured using industry classifications and participant self-reporting of ability to do their normal work with their present pain. Clinical effect was measured using the Patient Global Impression of Change measured at the 12 month follow-up assessment. Data were compared between groups using linear regression clustered by recruitment site. Bootstrap resampling was used to generate a visual representation of the 95% confidence interval for the incremental cost-effectiveness estimate. Two, one-way sensitivity analyses were undertaken to examine the robustness of findings to key assumptions. There were n = 38 participants in the intervention group who completed the 12 month assessment and n = 45 in the control. The intervention group had greater use of trial-related medical and therapy resources [$477 per participant (95% CI: $447, $508)], but lower use of non-trial medical and therapy resources [$-53 per participant (95% CI: $-105, $-0)], and a greater improvement in productivity [$-5123 per participant (95% CI: $-10,174, $-72)]. Overall, the intervention dominated with a saving of $478,100 and an additional 41 participants self-rating as being very or much improved compared to the control. There was >99% confidence in this finding of dominance in both the primary and sensitivity analyses. The motion-sensor biofeedback treatment approach in addition to guidelines- based care appears to be both more clinically effective and economically efficient than guidelines- based care alone. This approach appears to be a viable means to manage low back pain and further research in this area should be a priority. The randomised trial this research was based upon was prospectively registered on March 25th 2009 with the Australian New Zealand Clinical Trials Registry: ACTRN12609000157279 .

Twitter Demographics

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Mendeley readers

The data shown below were compiled from readership statistics for 91 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 91 100%

Demographic breakdown

Readers by professional status Count As %
Student > Master 21 23%
Student > Bachelor 11 12%
Student > Ph. D. Student 9 10%
Researcher 9 10%
Other 5 5%
Other 20 22%
Unknown 16 18%
Readers by discipline Count As %
Medicine and Dentistry 26 29%
Nursing and Health Professions 15 16%
Sports and Recreations 6 7%
Psychology 5 5%
Engineering 4 4%
Other 16 18%
Unknown 19 21%

Attention Score in Context

This research output has an Altmetric Attention Score of 1. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 28 September 2017.
All research outputs
#10,493,871
of 11,841,124 outputs
Outputs from BMC Musculoskeletal Disorders
#2,185
of 2,390 outputs
Outputs of similar age
#226,646
of 268,275 outputs
Outputs of similar age from BMC Musculoskeletal Disorders
#46
of 48 outputs
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