DiSCERN: Advanced PD Therapy Candidacy and Evaluation System

DiSCERN：先进 PD 治疗候选资格和评估系统

• 批准号: 10207343
• 负责人: Aaron John Hadley
• 金额: $ 80.27万
• 依托单位: GREAT LAKES NEUROTECHNOLOGIES
• 依托单位国家: 美国
• 财政年份: 2018
• 资助国家: 美国
• 起止时间: 2018-09-20 至 2024-06-30
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/10207343
• 关键词: Academic Medical Centers; Activities of Daily Living; Algorithms; Awareness; Caring; Cellular Phone; Cessation of life; Chronic; Clinic; Clinical; Clinical assessments; Collection; Communities; Computer software; Data; Data Collection; Decision Making; Deep Brain Stimulation; Detection; Development; Diagnosis; Disadvantaged; Dose; Dyskinetic syndrome; Emotional; Evaluation; Expert Systems; Fatigue; Feedback; Health; Health Care Costs; Health Technology; Healthcare; Home; Impaired cognition; Implant; Incidence; Institution; Lead; Letters; Levodopa; Measures; Medical; Methods; Modeling; Monitor; Motor; Movement Disorders; Neurology; Operative Surgical Procedures; Outcome; Parkinson Disease; Patient Selection; Patients; Perception; Pharmaceutical Preparations; Phase; Pilot Projects; Population; Process; Provider; Pump; Quality of life; Questionnaires; Resources; Risk; Rural; Rural Population; Screening procedure; Selection Bias; Self Assessment; Sensitivity and Specificity; Site; Specialist; Standardization; Symptoms; System; Technology; Telemedicine; Therapeutic; Unnecessary Surgery; Validation; Wireless Technology; base; compliance behavior; cost; data exchange; design; diagnostic platform; diaries; disparity reduction; exhaust; experience; health care delivery; health disparity; improved; innovation; mHealth; medical specialties; mobile application; motion sensor; motor disorder; motor symptom; new technology; novel; patient screening; predictive modeling; prevent; product development; racial minority; remote monitoring; remote screening; response; screening; side effect; smartphone Application; socioeconomics; success; therapy outcome; tool; wearable device; wearable sensor technology

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.

概括 目的是设计，开发和临床评估识别的标准化远程医疗工具 识别帕金森氏病（PD）的患者，他们将受益于先进疗法（AT）和 确定在接受者何时需要调整治疗。一旦长期使用PD用药会导致 运动波动和运动障碍以及所有非侵入性疗法都用尽了（例如，深脑 通常建议刺激，药水泵）。虽然学术医学中心的专家可能会适当 在候选人中识别，由于有限的有限评估的访问和不平等的利用，AT被未被充分利用 PD人群相当大的子集的资源。远程筛选和监视会将 改善患者的选择，减少分布并扩大人口的访问权限并灾难 社区。该系统将吸引并授权患者，提供者和医疗机构，并导致 改善了健康，医疗保健服务以及健康差异的减少。这种移动健康技术将 包括患者友好的智能手机应用程序，非运动评估以及用于无线可穿戴传感器 不断监测PD运动症状，并发症和生活质量（QOL）。我们以前有 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， 这将大大降低该项目的风险。尽管如此，需要新颖的发展和验证工作才能 商业化这项新技术。创新包括：1）PD监视算法与 上下文意识活动检测可改善PD运动评估和QOL定量； 2）实施 智能手机和可穿戴设备上的算法； 3）开发使用电动机的预测模型 和非运动功能，可以准确识别PD患者，这些患者将成为AT的良好候选者；和4） 实施一个模型，该模型会在接受者需要调整治疗时提醒临床医生。通过 与AT系统集成，辨别将改善临床体验，并允许有限的可用性 专家将护理扩展到转移和不断增长的PD人群，否则他们可能无法获得AT。 第一阶段包括：1）对PD患者数据的上下文意识活动检测算法的验证； 2）确定 特定活动或活动水平与PD QoL相关； 3）使用临床反馈来识别 收集的数据功能可用于告知临床决策； 4）识别可穿戴设备 在最终系统中使用。第二阶段包括：1）上下文意识活动检测和PD症状的过渡 定量算法和可穿戴芯片上的算法； 2）开发智能手机应用程序 集成数据收集，非运动评估以及对云的数据传输； 3）从 在AT之前和之后的几个月中，在候选人中发起了准确识别的模型 候选人以及需要进行调整时。识别将提高治疗效率，扩大访问权限， 并导致更多的患者选择AT。