Digital Care for Chronic Musculoskeletal Pain: A 10,000 User Longitudinal Study Demonstrating Efficacy and Scalability

Abstract

Background: Chronic musculoskeletal pain has a vast global prevalence and economic burden. Conservative therapies are universally recommended but require patient engagement and self-management to be effective. In this study, we assessed engagement behaviors and subject-reported outcomes in subjects with chronic low back or knee pain who participated in a 12-week digital care pathway (DCP). Methods: Subjects participated in a 12-week multi-modal DCP administered via a mobile app incorporating education, sensor-guided exercise therapy, and behavioral health support with 1-on-1 remote health coaching. Primary outcome was VAS pain. Secondary measures included engagement levels, program completion, program satisfaction, condition-specific pain measures, depression, anxiety, and work productivity. Findings: Of 10,264 participants with chronic back or knee pain, 73% completed the DCP into the final month. 79% of these participants (70% of all participants) achieved minimally important change in pain. Mean improvement in VAS pain was 68% and the number of exercise therapy sessions and coaching interactions were both positively associated with improvement in pain, supporting that the amount of engagement influenced VAS pain outcomes. Secondary outcomes included 58% decrease in both depression and anxiety scores, and 62% improvement in work productivity. Lastly, three groups with distinct longitudinal pain response behaviors were identified and could be predicted from baseline measures with 76% accuracy. Interpretation: This is the first longitudinal digital health study to analyze musculoskeletal pain outcomes in a sample of this magnitude, supporting the efficacy and safety of using a digital care approach in a large, real-world population. Participants demonstrated high completion and engagement rates, and a significant positive relationship between engagement and pain reduction was identified, a finding not previously demonstrated in a DCP. Furthermore, the large sample size allowed for identification of distinct pain response subgroups which may prove beneficial in predicting recovery and tailoring future interventions. Funding Statement: Hinge Health, Inc. Declaration of Interests: Authors Bailey and Agarwal were academic collaborators on this study and were paid as consultants for their expertise for conducting this study. Bailey and Agarwal had unrestricted access to the data and lead the analysis and interpretation of the results. Author Krauss works at Hinge Health, Inc., and receives salary and equity compensation. Subsequent to paper completion, author Agarwal became employed at Hinge Health, Inc., and receives salary and equity compensation. Ethics Approval Statement: The trial was approved by the Western Institutional Review Board and complied with all ethical regulations.