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ICLIC-MS for Enhancing Outcomes Research and Clinical Care in Multiple Sclerosis

ICLIC-MS 增强多发性硬化症的结果研究和临床护理

基本信息

批准号：
9763663
负责人：
LISA F BARCELLOS
金额：
$ 60.6万
依托单位：
UNIVERSITY OF CALIFORNIA BERKELEY
依托单位国家：
美国
项目类别：
财政年份：
2018
资助国家：
美国
起止时间：
2018-08-14 至 2023-05-31
项目状态：
已结题

来源：
https://reporter.nih.gov/project-details/9763663
关键词：
Address Area Big Data Biological Biology Biometry California Clinic Clinic Visits Clinical Clinical Data Clinical Investigator Clinical Research Clinical assessments Cognition Cognitive Collection Comorbidity Consumption Data Data Collection Development Disease Disease Progression Electronic Health Record Employment Employment Status Environmental Exposure Epidemiologic Methods Ethnic Origin Family Female Funding Opportunities Genetic Genomics Goals Health Health Maintenance Organizations Impaired cognition Individual Internet Intervention Lead Light Machine Learning Magnetic Resonance Imaging Measures Mental Depression Methods Multiple Sclerosis Neurologist Neurology Outcome Outcome Measure Outcome Study Outcomes Research Pathogenesis Patient Care Patient-Focused Outcomes Patients Performance Physically Handicapped Physicians Pilot Projects Population Predictive Factor Preparation Prevention strategy Primary Health Care Progressive Disease Quality of life Race Recording of previous events Reporting Research Resources Risk Factors Sampling Source Structure Technology Testing Time Unemployment Validity and Reliability Visit Work base clinical care cognitive function cohort disability electronic data health plan human genomics improved male member multidisciplinary multiple sclerosis patient new technology prevent programs response sex web based interface web-based tool

项目摘要

PROJECT SUMMARY Cognitive impairment, physical disability and progressive disease are common but understudied clinical outcomes that substantially impact employment and overall quality of life for individuals with multiple sclerosis (MS). We have recently developed and validated an assisted, web-based tool (ICLIC-MS) for systematic and longitudinal clinical outcomes data collection of MS-validated cognitive function measures, physical disability and progressive disease measures that are not reliably captured in the electronic health record (EHR). In response to FOA# PA-17-010, Use of Technology to Enhance Patient Outcomes and Prevent Illness, our team proposes the study of MS outcomes in a large, multi-ethnic population representative sample of more than 3,000 female and male MS cases from the Kaiser Permanente Northern California Health Plan Membership. We will integrate other EHR data such as important comorbid conditions, use of disease modifying therapy, MRI reports, as well as quality of life measures and employment histories. Our goals include: 1) comprehensively characterizing clinical outcomes in a large MS patient cohort; 2) developing and utilizing an integrated MS health report to enhance patient care; and 3) establishing a resource for clinical outcomes research in MS that also includes whole genomic and environmental exposure data. Findings from our proposed study represent an extraordinary opportunity to facilitate effective long-term management of MS, accelerate progress in the understanding of disease pathogenesis, predict patient trajectories and inform prevention strategies. We have assembled a team with strong expertise in clinical neurology/MS neurology, advanced epidemiologic methods, EHR structure and clinical care within a health maintenance organization, human genomics, biostatistics, and big data approaches.

项目概要认知障碍、身体残疾和进行性疾病很常见，但尚未得到充分研究显着影响个人就业和整体生活质量的临床结果患有多发性硬化症（MS）。我们最近开发并验证了一个基于网络的辅助工具工具 (ICLIC-MS)，用于系统性和纵向临床结果数据收集，并经过 MS 验证认知功能测量、身体残疾和进行性疾病测量可靠地记录在电子健康记录 (EHR) 中。响应 FOA# PA-17-010，使用我们的团队提出了这项研究，旨在利用技术来提高患者的治疗效果和预防疾病超过 3,000 人的大型多种族人群代表性样本中的 MS 结果来自 Kaiser Permanente 北加州健康计划的女性和男性多发性硬化症病例会员资格。我们将整合其他 EHR 数据，例如重要的合并症、使用疾病修饰治疗、MRI 报告以及生活质量测量和就业历史。我们的目标包括：1) 全面表征大型 MS 的临床结果患者队列； 2) 开发和利用综合多发性硬化症健康报告来加强患者护理； 3) 建立多发性硬化症临床结果研究资源，其中还包括整个基因组和环境暴露数据。我们提出的研究结果代表了促进多发性硬化症长期有效管理、加速进展的绝佳机会了解疾病发病机制、预测患者轨迹并为预防提供信息策略。我们组建了一支在临床神经病学/多发性硬化症神经病学方面拥有丰富专业知识的团队，健康维护领域的先进流行病学方法、EHR 结构和临床护理组织、人类基因组学、生物统计学和大数据方法。