Methods Core

方法学核心的目标是支持高影响力的临床研究，重点是 肌肉骨骼疾病的诊断、治疗和预防。具体地说， 方法论核心将提供现代数据科学基础设施 利用电子健康记录(EHR)的研究，以及收集患者报告的试验 结果。我们将围绕两大主题组织多项活动： 验证性学习，包括设计和分析观察性研究和 随机试验；以及预测性学习，它利用当代机器学习和 用于处理电子健康档案数据等高维数据的人工智能 信息。数据科学正在推动临床研究的创新，与 多个电子病历系统为大规模临床学习打开了新的机会。最终 严格的研究需要新的方法来提取可靠的信息，并要求 试验设计可以根据患者的独特特征和背景进行调整 医疗保健提供系统。华盛顿大学生物医学统计中心 (CBS)为多个观测和统计机构提供了信息学和统计方面的领导 专注于肌肉骨骼疾病的随机研究，具有独特的地位 在NIAMS任务的广泛范围内扩大影响的基础。

The goal of the Methodologic Core is to support high-impact clinical research focusing on the diagnosis, treatment, and prevention of musculoskeletal diseases. Specifically, the Methodologic Core will provide the contemporary data science infrastructure necessary for studies that leverage electronic health records (EHR), and for trials that collect patient reported outcomes. We will organize around two major themes encompassing multiple activities: confirmatory learning which includes design and analysis of observational studies and randomized trials; and predictive learning which leverages contemporary machine learning and artificial intelligence for processing electronic health records data and other high-dimensional information. The data sciences are driving innovation in clinical research with the linkage of multiple EMR systems opening new opportunities for large-scale clinical learning. Ultimately rigorous research demands new methods for the extraction of reliable information and requires the design of trials that can tailor to the unique characteristics of patients and the context of health care delivery systems. The University of Washington Center for Biomedical Statistics (CBS) has provided informatics and statistical leadership to multiple observational and randomized studies focusing on musculoskeletal disorders and is uniquely positioned to provide the foundation for expanded impact within the broad scope of the NIAMS mission.