国家COVID队列协作数据增强:扩展共同数据模型的途径
Kellie M Walters1, Marshall Clark1, Sofia Dard1
1NC TraCS Institute, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, United States.
Journal of the American Medical Informatics Association : JAMIA
|November 23, 2024
概括
在国家COVID队列协作 (N3C) 中长期COVID研究的数据增强提高了数据实用性. 标准化的项目驱动数据建模通过与常见数据模型保持一致来支持长期的COVID研究.
科学领域:
- 医疗信息学 医疗信息学
- 临床研究数据管理数据管理
背景情况:
- 国家COVID队列协作 (N3C) 需要强大的数据来进行长期的COVID研究.
- 现有的常用数据模型可能无法完全捕捉长期COVID的特定研究需求.
研究的目的:
- 为N3C开发和实施数据增强,以支持长期COVID研究.
- 为数据丰富提供标准化指导.
主要方法:
- 为特定的长期COVID研究需求创建数据设计.
- 定义了范围,并为数据准备和人口提供了指导.
- 确保与共同的数据模型规范和术语标准保持一致.
主要成果:
- 截至2024年6月,29个贡献站点在其N3C数据管道中集成了至少一个数据增强.
- 开发了项目特定的数据建模指南和文档.
结论:
- 项目驱动的数据增强对于满足超越常见数据模型的特定研究需求至关重要.
- 标准化数据增强提高了N3C等大型研究协作中的数据适合目的.
- 这种方法有助于快速开发定制的数据资源,用于关键的研究领域,如长期COVID.
相关概念视频
Statistical Methods for Analyzing Epidemiological Data
305
Epidemiological data primarily involves information on specific populations' occurrence, distribution, and determinants of health and diseases. This data is crucial for understanding disease patterns and impacts, aiding public health decision-making and disease prevention strategies. The analysis of epidemiological data employs various statistical methods to interpret health-related data effectively. Here are some commonly used methods:
305
Principles of Disease Surveillance
69
Disease surveillance is the systematic collection, analysis, and interpretation of health data essential to the planning, implementation, and evaluation of public health practice. This process integrates data dissemination to entities responsible for preventing and controlling disease, injury, and disability. Surveillance systems provide crucial information for action, helping public health authorities make informed decisions to manage and prevent outbreaks, ensure public safety, optimize...
69
Model-Independent Approaches for Pharmacokinetic Data: Noncompartmental Analysis
47
Noncompartmental analyses offer an alternative method for describing drug pharmacokinetics without relying on a specific compartmental model. In this approach, the drug's pharmacokinetics are assumed to be linear, with the terminal phase log-linear. This assumption allows for simplified analysis and interpretation of the drug's behavior in the body.
One important characteristic of noncompartmental analyses is that drug exposure increases proportionally with increasing doses. This...
One important characteristic of noncompartmental analyses is that drug exposure increases proportionally with increasing doses. This...
47
Model Approaches for Pharmacokinetic Data: Compartment Models
77
Compartmental analysis is a widely adopted approach to characterizing drug pharmacokinetics. It uses compartment models that conceptualize the body as a collection of reversibly communicating compartments, each representing a group of tissues exhibiting similar drug distribution characteristics. The movement rate of the drug between these compartments is typically described by first-order kinetics.
Two primary types of compartment models are recognized: mammillary and catenary. The more...
Two primary types of compartment models are recognized: mammillary and catenary. The more...
77
Model Approaches for Pharmacokinetic Data: Distributed Parameter Models
58
Pharmacokinetic models are mathematical constructs that represent and predict the time course of drug concentrations in the body, providing meaningful pharmacokinetic parameters. These models are categorized into compartment, physiological, and distributed parameter models.
The distributed parameter models are specifically designed to account for variations and differences in some drug classes. This model is particularly useful for assessing regional concentrations of anticancer or...
The distributed parameter models are specifically designed to account for variations and differences in some drug classes. This model is particularly useful for assessing regional concentrations of anticancer or...
58
Longitudinal Studies
133
Longitudinal studies are also widely used in other medical and social science fields. For instance, in cardiovascular research, they can monitor patients' health over decades to identify risk factors for heart disease, such as high cholesterol or smoking, and evaluate the long-term effectiveness of preventive measures. Similarly, in mental health studies, researchers might follow individuals from adolescence into adulthood to understand the development and progression of conditions like...
133


