DiSCERN: Advanced PD Therapy Candidacy and Evaluation System

摘要 目标是设计、开发和临床评估识别，这是一种标准化的远程医疗工具，用于 确定哪些帕金森氏病(PD)患者将受益于先进治疗(AT)和 确定接受AT治疗的患者何时需要调整治疗。一旦慢性帕金森病药物使用导致 运动波动和运动障碍以及所有非侵入性治疗都已用尽，AT(例如，大脑深部 刺激、药物泵)通常被推荐使用。而学术医学中心的专家可能会适当地 确定AT候选人，由于有限的访问和对有限的评估的不公平使用，AT未得到充分利用 为PD人口中相当大的子集提供资源。以敏锐的意志进行远程筛查和监控 改善患者选择，缩小差距，扩大农村人口和弱势群体的准入 社区。该系统将吸引和支持患者、提供者和医疗机构，并导致 改善健康、医疗保健提供，缩小健康差距。这项移动医疗技术将 包括患者友好的智能手机应用程序、非机动评估和无线可穿戴传感器 持续监测帕金森病患者的运动症状、并发症和生活质量。我们之前已经 商业化的可穿戴设备和移动应用程序，用于远程监控PD电机症状和副作用， 这将大大降低项目的风险。尽管如此，仍需要新的开发和验证努力来 将这项新技术商业化。创新包括：1)将局部放电监测算法与 情境感知活动检测用于改进的PD运动评估和QOL量化；2)实施 在智能手机和可穿戴设备上的算法；3)开发使用电机的预测模型 和非运动特征，以准确地识别哪些PD患者适合进行AT；以及4) 实施一种模式，当AT接受者需要治疗调整时提醒临床医生。穿过 与AT系统的集成，Discern将改善临床医生的体验，并允许有限的 专家将护理范围扩大到多样化和不断增长的帕金森病人群，否则他们可能无法获得AT。 第一阶段包括：1)验证PD患者数据上的上下文感知活动检测算法；2)确定 具体活动或活动水平与PD QOL相关的程度；3)使用临床医生的反馈来确定 收集的数据特征有助于为AT临床决策提供信息；以及4)识别要 在最终系统中使用。第二阶段包括：1)情景感知活动检测和PD症状的过渡 将算法量化到智能手机和可穿戴芯片上；2)开发一款智能手机应用程序， 将数据收集、非机动评估和数据传输集成到云中；以及3)从 AT候选人在AT启动之前和之后的几个月中开发准确识别AT的模型 候选人以及需要调整AT的时间。识别力将提高治疗效率，扩大治疗渠道， 并导致更多的患者选择AT。

Summary The objective is to design, develop, and clinically assess DiSCERN, a standardized telemedicine tool for identifying patients with Parkinson’s disease (PD) who would benefit from advanced therapies (AT) and determining when AT recipients need therapy adjustments. Once chronic PD medication usage results in motor fluctuations and dyskinesias and all non-invasive therapies have been exhausted, AT (e.g., deep brain stimulation, drug pumps) is often recommended. While experts at academic medical centers may appropriately identify AT candidates, AT is underutilized due to limited access and inequitable utilization of limited evaluative resources for a sizable subset of the PD population. Remote screening and monitoring with DiSCERN will improve patient selection, reduce disparities, and expand access for rural populations and disadvantaged communities. The system will engage and empower patients, providers, and healthcare institutions and lead to improved health, healthcare delivery, and the reduction of health disparities. This mobile health technology will include a patient friendly smartphone app, non-motor assessments, and wireless wearable sensors for continuously monitoring PD motor symptoms, complications, and quality of life (QoL). We have previously commercialized wearables and mobile apps for remote monitoring of PD motor symptoms and side effects, which will significantly de-risk the project. Still, novel development and validation efforts are required to commercialize this new technology. Innovations include: 1) integration of PD monitoring algorithms with context aware activity detection for improved PD motor assessment and QoL quantification; 2) implementation of the algorithms on a smartphone and wearable device; 3) development of a predictive model that uses motor and non-motor features to accurately identify PD patients who would be good candidates for AT; and 4) implementation of a model that alerts clinicians when an AT recipient needs a therapy adjustment. Through integration with AT systems, DiSCERN will improve the clinician experience and allow the limited availability of specialists to scale care to a diverse and growing PD population, who may not otherwise have access to AT. Phase I includes: 1) validation of context aware activity detection algorithms on PD patient data; 2) determining the extent specific activities or activity levels correlate with PD QoL; 3) using clinician feedback to identify collected data features that are useful in informing AT clinical decisions; and 4) identification of wearables to be used in the final system. Phase II includes: 1) transition of context aware activity detection and PD symptom quantification algorithms onto a smartphone and wearable chips; 2) development of a smartphone app that integrates data collection, non-motor assessment, and data-transfer to the cloud; and 3) collecting data from AT candidates in the months before and after AT is initiated to develop models that accurately identify AT candidates and when AT adjustments are needed. DiSCERN will improve therapy efficiency, expand access, and result in more patients opting for AT.