Medical App Treatment of Non-Specific Low Back Pain in the 12-month Cluster-Randomized Controlled Trial Rise-uP: Where Clinical Superiority Meets Cost Savings

Janosch A. Priebe, Linda Kerkemeyer, Katharina K. Haas, Katharina Achtert, Leida F.Moreno Sanchez, Paul Stockert, Maximilian Spannagl, Julia Wendlinger, Reinhard Thoma, Siegfried Ulrich Jedamzik, Jan Reichmann, Sebastian Franke, Leonie Sundmacher, Volker E. Amelung, Thomas R. Toelle

Research output: Contribution to journalArticlepeer-review

3 Scopus citations

Abstract

Purpose: Non-specific low back pain (NLBP) exerts a profound impact on global health and economics. In the era of Web 3.0, digital therapeutics offer the potential to improve NLBP management. The Rise-uP trial introduces a digitally anchored, general practitioner (GP)-focused back pain management approach with the Kaia back pain app as the key intervention. Here, we present the 12-months evaluation of the Rise-uP trial including clinical and economic outcomes, patient satisfaction and behavioral tracking analysis. Methods: The cluster-randomized controlled study (registration number: DRKS00015048) enrolled 1237 patients, with 930 receiving treatment according to the Rise-uP approach and 307 subjected to standard of care treatment. Assessments of pain, psychological state, functional capacity, and well-being (patient-reported outcome measures; PROMs) were collected at baseline, and at 3-, 6-, and 12-months follow-up intervals. Health insurance partners AOK, DAK, and BARMER provided individual healthcare cost data. An artificial intelligence (AI)-driven behavioral tracking analysis identified distinct app usage clusters that presented all with about the same clinical outcome. Patient satisfaction (patient-reported experience measures; PREMs) was captured at the end of the trial. Results: Intention-to-treat (ITT) analysis demonstrated that the Rise-uP group experienced significantly greater pain reduction at 12 months compared to the control group (IG: −46% vs CG: −24%; p < 0.001) with only the Rise-uP group achieving a pain reduction that was clinically meaningful. Improvements in all other PROMs were notably superior in patients of the Rise-uP group. The AI analysis of app usage discerned four usage clusters. Short-to long-term usage, all produced about the same level of pain reduction. Cost-effectiveness analysis indicated a substantial economic benefit for Rise-uP. Conclusion: The Rise-uP approach with a medical multimodal back pain app as the central element of digital treatment demonstrates both, clinical and economic superiority compared to standard of care in the management of NLBP.

Original languageEnglish
Pages (from-to)2239-2255
Number of pages17
JournalJournal of Pain Research
Volume17
DOIs
StatePublished - 2024

Keywords

  • behavioral tracking analysis
  • digital medicine
  • healthcare costs
  • medical apps
  • multimodal pain therapy
  • non-specific low back pain

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