PDF(Pubmed)
Abstract：
UNASSIGNED: 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.
UNASSIGNED: 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.
UNASSIGNED: 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.
UNASSIGNED: 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.
UNASSIGNED: 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.
UNASSIGNED: 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.
UNASSIGNED: 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.
摘要：
■非特异性下腰痛（NLBP）对全球卫生和经济产生了深远的影响。在Web3.0时代，数字疗法提供了改善NLBP管理的潜力。Rise-uP试验引入了数字锚定，以全科医生（GP）为重点的背痛管理方法，以Kaia背痛应用程序为关键干预措施。这里,我们介绍了Rise-uP试验的12个月评估，包括临床和经济结果，患者满意度和行为跟踪分析。
■集群随机对照研究（注册号：DRKS00015048）纳入了1237名患者，其中930人根据Rise-uP方法接受治疗，307人接受标准护理治疗。疼痛的评估，心理状态,功能能力，和健康（患者报告的结果测量；PROM）在基线时收集，在3-，6-，和12个月的随访间隔。健康保险合作伙伴AOK，DAK,BARMER提供了个人医疗保健成本数据。人工智能（AI）驱动的行为跟踪分析确定了不同的应用程序使用集群，这些集群呈现的临床结果大致相同。在试验结束时捕获患者满意度(患者报告的经验测量;PREM)。
■意向治疗（ITT）分析表明，与对照组相比，Rise-uP组在12个月时的疼痛减轻幅度显着较大（IG：-46％vsCG：-24％；p<0.001），只有Rise-uP组的疼痛减轻才具有临床意义。在Rise-uP组患者中，所有其他PROM的改善均显着优于此。对应用程序使用情况的AI分析区分了四个使用集群。短期到长期使用，都产生了相同程度的疼痛减轻。成本效益分析表明，Rise-uP具有巨大的经济效益。
■以医疗多模式背痛应用程序作为数字治疗的核心要素的Rise-uP方法证明了这两者，在NLBP的管理中，与标准护理相比具有临床和经济优势。
■集群随机对照研究（注册号：DRKS00015048）纳入了1237名患者，其中930人根据Rise-uP方法接受治疗，307人接受标准护理治疗。疼痛的评估，心理状态,功能能力，和健康（患者报告的结果测量；PROM）在基线时收集，在3-，6-，和12个月的随访间隔。健康保险合作伙伴AOK，DAK,BARMER提供了个人医疗保健成本数据。人工智能（AI）驱动的行为跟踪分析确定了不同的应用程序使用集群，这些集群呈现的临床结果大致相同。在试验结束时捕获患者满意度(患者报告的经验测量;PREM)。
■意向治疗（ITT）分析表明，与对照组相比，Rise-uP组在12个月时的疼痛减轻幅度显着较大（IG：-46％vsCG：-24％；p<0.001），只有Rise-uP组的疼痛减轻才具有临床意义。在Rise-uP组患者中，所有其他PROM的改善均显着优于此。对应用程序使用情况的AI分析区分了四个使用集群。短期到长期使用，都产生了相同程度的疼痛减轻。成本效益分析表明，Rise-uP具有巨大的经济效益。
■以医疗多模式背痛应用程序作为数字治疗的核心要素的Rise-uP方法证明了这两者，在NLBP的管理中，与标准护理相比具有临床和经济优势。
