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Janosch A Priebe,1 Linda Kerkemeyer,2 Katharina K Haas,1 Katharina Achtert,2 Leida F Moreno Sanchez,1,3 Paul Stockert,1 Maximilian Spannagl,1 Julia Wendlinger,1 Reinhard Thoma,4 Siegfried Ulrich Jedamzik,3 Jan Reichmann,5 Sebastian Franke,6 Leonie Sundmacher,6 Volker E Amelung,2 Thomas R Toelle1 1Center of Interdisciplinary Pain Medicine, Department of Neurology, Klinikum Rechts der Isar, Technical University of Munich (TUM), Munich, Germany; 2Institute for Applied Health Services Research, Inav GmbH, Berlin, Germany; 3Bayerische TelemedAllianz, Ingolstadt, Baar-Ebenhausen, Germany; 4Pain Clinic, Algesiologikum Pain Center, Munich, Germany; 5StatConsult GmbH Magdeburg, Magdeburg, Germany; 6Department of Health Economics, Faculty of Sports and Health Sciences, Technical University of Munich (TUM), Munich, GermanyCorrespondence: Thomas R Toelle, Center of Interdisciplinary Pain Medicine, Department of Neurology, Klinikum rechts der Isar, Technical University of Munich (TUM), Ismaninger Str. 22, Munich, 81675, Germany, Tel +49-89-4140-4613, Email thomas.toelle@tum.dePurpose: 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.Keywords: digital medicine, medical apps, non-specific low back pain, multimodal pain therapy, healthcare costs, behavioral tracking analysis

Janosch A Priebe,1 Katharina K Haas,1 Leida F Moreno Sanchez,1,2 Karin Schoefmann,1 Daniel A Utpadel-Fischler,1 Paul Stockert,1 Reinhard Thoma,3 Christine Schiessl,3 Linda Kerkemeyer,4 Volker Amelung,4 Siegfried Jedamzik,2 Jan Reichmann,5 Ursula Marschall,6 Thomas R Toelle1 1Center of Interdisciplinary Pain Medicine, Department of Neurology, Klinikum Rechts der Isar, Technical University of Munich, Munich, Germany; 2Bayerische TelemedAllianz (BTA), Ingolstadt, Germany; 3Pain Clinic, Algesiologikum Pain Center, Munich, Germany; 4Institute for Applied Health Services Research, inav GmbH, Berlin, Germany; 5StatConsult GmbH Magdeburg, Magdeburg, Germany; 6Barmer Hauptverwaltung, Wuppertal, GermanyCorrespondence: Thomas R ToelleCenter of Interdisciplinary Pain Medicine, Department of Neurology, Klinikum Rechts der Isar, Technische Universität München, Ismaninger Str. 22, Munich 81675, GermanyTel +49-89-4140-4613Email thomas.toelle@tum.dePurpose: Non-specific low back pain (NLBP) causes an enormous burden to patients and tremendous costs for health care systems worldwide. Frequently, treatments are not oriented to existing guidelines. In the future, digital elements may be promising tools to support guideline-oriented treatment in a broader range of patients. The cluster-randomized controlled “Rise-uP” trial aims to support a General Practitioner (GP)-centered back pain treatment (Registration No: DRKS00015048) and includes the following digital elements: 1) electronic case report form (eCRF), 2) a treatment algorithm for guideline-based clinical decision making of GPs, 3) teleconsultation between GPs and pain specialists for patients at risk for development of chronic back pain, and 4) a multidisciplinary mobile back pain app for all patients (Kaia App).Methods: In the Rise-uP trial, 111 GPs throughout Bavaria (southern Germany) were randomized either to the Rise-uP intervention group (IG) or the control group (CG). Rise-uP patients were treated according to the guideline-oriented Rise-uP treatment algorithm. Standard of care was applied to the CG patients with consideration given to the “National guideline for the treatment of non-specific back pain”. Pain rating on the numeric rating scale was the primary outcome measure. Psychological measures (anxiety, depression, stress), functional ability, as well as physical and mental wellbeing, served as secondary outcomes. All values were assessed at the beginning of the treatment and at 3-month follow-ups.Results: In total, 1245 patients (IG: 933; CG: 312) with NLBP were included in the study. The Rise-uP group showed a significantly stronger pain reduction compared to the control group after 3 months (IG: M=− 33.3% vs CG: M=− 14.3%). The Rise-uP group was also superior in secondary outcomes. Furthermore, high-risk patients who received a teleconsultation showed a larger decrease in pain intensity (− 43.5%) than CG patients (− 14.3%). ANCOVA analysis showed that the impact of teleconsultation was mediated by an increased training activity in the Kaia App.Conclusion: Our results show the superiority of the innovative digital treatment algorithm realized in Rise-uP, even though the CG also received relevant active treatment by their GPs. This provides clear evidence that digital treatment may be a promising tool to improve the quality of treatment of non-specific back pain. In 2021, analyses of routine data from statutory health insurances will enable us to investigate the cost-effectiveness of digital treatment.Keywords: NLBP, eHealth, mHealth, digital medicine, guideline-oriented treatment, chronic pain, STarT Back

Byline: U. Martin (1), J. Fuhl (2), I. Gaspard (3), A. Kuchar (2), A.F. Molisch (2), R. Thoma (4) Keywords: mobile radio channel; direction of arrival; smart antennas; diversity Abstract: Intelligent antennas offer the possibility of greatly increasing the capacity of cellular mobile radio systems. We give a comprehensive overview of the literature concerning model scenarios for applications of direction-selective intelligent antennas. Measurement campaigns and simplified models are described that have been derived from these measurements or from physical considerations. Furthermore, directional fading simulators are reviewed which are essential for testing of smart antenna systems. Author Affiliation: (1) Fachhochschule Mannheim, USA (2) TU Wien, INTHFT, Austria (3) Deutsche Telekom AG, Technologiezentrum, Germany (4) TU Ilmenau, Fachgruppe Elektronische Messtechnik, Germany Article History: Registration Date: 14/10/2004