Background: Multiple Sclerosis Partners Advancing Technology and Health Solutions (MS PATHS) is the first example of a learning health system in multiple sclerosis (MS). This paper describes the initial implementation of MS PATHS and initial patient characteristics. Methods: MS PATHS is an ongoing initiative conducted in 10 healthcare institutions in three countries, each contributing standardized information acquired during routine care. Institutional participation required the following: active MS patient census of ≥500, at least one Siemens 3T magnetic resonance imaging scanner, and willingness to standardize patient assessments, share standardized data for research, and offer universal enrolment to capture a representative sample. The eligible participants have diagnosis of MS, including clinically isolated syndrome, and consent for sharing pseudonymized data for research. MS PATHS incorporates a self-administered patient assessment tool, the Multiple Sclerosis Performance Test, to collect a structured history, patient-reported outcomes, and quantitative testing of cognition, vision, dexterity, and walking speed. Brain magnetic resonance imaging is acquired using standardized acquisition sequences on Siemens 3T scanners. Quantitative measures of brain volume and lesion load are obtained. Using a separate consent, the patients contribute DNA, RNA, and serum for future research. The clinicians retain complete autonomy in using MS PATHS data in patient care. A shared governance model ensures transparent data and sample access for research. Results: As of August 5, 2019, MS PATHS enrolment included participants (n = 16,568) with broad ranges of disease subtypes, duration, and severity. Overall, 14,643 (88.4%) participants contributed data at one or more time points. The average patient contributed 15.6 person-months of follow-up (95% CI: 15.5-15.8); overall, 166,158 person-months of follow-up have been accumulated. Those with relapsing-remitting MS demonstrated more demographic heterogeneity than the participants in six randomized phase 3 MS treatment trials. Across sites, a significant variation was observed in the follow-up frequency and the patterns of disease-modifying therapy use. Conclusions: Through digital health technology, it is feasible to collect standardized, quantitative, and interpretable data from each patient in busy MS practices, facilitating the merger of research and patient care. This approach holds promise for data-driven clinical decisions and accelerated systematic learning.

中文翻译：

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利用现实世界的数据来指导决策：多个硬化症合作伙伴正在推进技术和健康解决方案（MS PATHS）。

背景：先进的技术和健康解决方案（MS PATHS）的多发性硬化症合作伙伴是多发性硬化症（MS）中学习健康系统的第一个示例。本文介绍了MS PATHS的初始实施方式和初始患者特征。方法：MS PATHS是在三个国家/地区的10个医疗机构中进行的一项持续性计划，每个机构都提供在常规护理期间获得的标准化信息。机构参与需要以下条件：≥500的活跃MS患者普查，至少一台Siemens 3T磁共振成像扫描仪，愿意标准化患者评估，共享标准化数据以进行研究并提供通用注册以采集代表性样品。符合条件的参与者可以诊断为MS，包括临床孤立的综合征，并同意共享用于研究的假名数据。MS PATHS集成了自我管理的患者评估工具多发性硬化症表现测试，以收集结构化的病史，患者报告的结果以及对认知能力，视力，灵活性和步行速度的定量测试。脑磁共振成像是使用Siemens 3T扫描仪上的标准化采集序列采集的。获得定量的脑容量和病变负荷。在获得单独同意的情况下，患者会贡献DNA，RNA和血清，以供将来研究之用。临床医生保留在患者护理中使用MS PATHS数据的完全自主权。共享的治理模型可确保透明的数据和用于研究的样本访问。结果：截至2019年8月5日，MS PATHS纳入研究的参与者（n = 16,568）具有广泛的疾病亚型，持续时间和严重性。总体而言，有14643（88.4％）位参与者在一个或多个时间点贡献了数据。平均患者接受了15.6人-月的随访（95％CI：15.5-15.8）；总体而言，已累计进行了166,158人月的随访。那些患有复发缓解型MS的患者比六个随机的3期MS治疗试验的参与者表现出更大的人口统计学异质性。在各个部位，随访频率和疾病改变疗法的使用方式均观察到显着变化。结论：通过数字医疗技术，在繁忙的MS实践中从每位患者收集标准化，定量和可解释的数据是可行的，从而促进了研究和患者护理的合并。这种方法为以数据为依据的临床决策和加速系统学习提供了希望。