TY - JOUR
T1 - Medical App Treatment of Non-Specific Low Back Pain in the 12-month Cluster-Randomized Controlled Trial Rise-uP
T2 - Where Clinical Superiority Meets Cost Savings
AU - Priebe, Janosch A.
AU - Kerkemeyer, Linda
AU - Haas, Katharina K.
AU - Achtert, Katharina
AU - Sanchez, Leida F.Moreno
AU - Stockert, Paul
AU - Spannagl, Maximilian
AU - Wendlinger, Julia
AU - Thoma, Reinhard
AU - Jedamzik, Siegfried Ulrich
AU - Reichmann, Jan
AU - Franke, Sebastian
AU - Sundmacher, Leonie
AU - Amelung, Volker E.
AU - Toelle, Thomas R.
N1 - Publisher Copyright:
© 2024 Priebe et al.
PY - 2024
Y1 - 2024
N2 - 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.
AB - 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.
KW - behavioral tracking analysis
KW - digital medicine
KW - healthcare costs
KW - medical apps
KW - multimodal pain therapy
KW - non-specific low back pain
UR - http://www.scopus.com/inward/record.url?scp=85197864845&partnerID=8YFLogxK
U2 - 10.2147/JPR.S473250
DO - 10.2147/JPR.S473250
M3 - Article
AN - SCOPUS:85197864845
SN - 1178-7090
VL - 17
SP - 2239
EP - 2255
JO - Journal of Pain Research
JF - Journal of Pain Research
ER -