真实世界数据:好处、限制和未来

真实的数据 (RWD) are broadly defined as data that have been collected as part of health care delivery and includes electronic health records (EHRs), 保险理赔数据库, 以及特定疾病的登记. 虽然这些数据来源的设计并没有考虑到研究, advances in data infrastructure have led to a growing interest in using them to answer emerging research questions. 我们问了凯文·威尔逊, PhD, a 趣赢平台 Associate Director who leads and coordinates 趣赢平台’s Data Science Group, 浏览有关RWD的最新资讯.

Q. What are RWD?

A. RWD数据来源于多个数据源, such as EHRs, 保险索赔, 疾病登记, 可穿戴设备, 行政记录, 产品消费, 还有社交媒体. 当这些现有的资源, 哪些是为特定目的收集的, 用于研究, 它们被称为“真实世界的数据”.”

Q. 应用RWD解决客户问题的好处是什么?

A. One important benefit to using RWD is that it allows us to access large datasets more rapidly and less expensively. This is particularly important at a time when survey response rates are declining because we don’t have to recruit and interview participants. As an example, RWD were very useful in meeting the unprecedented challenge of COVID-19 because they enabled public health agencies to understand quickly the incidence and severity of the virus and rapidly develop vaccines and drugs to combat it. 在其他领域，美国政府也采取了类似的措施.S. 美国食品和药物管理局使用RWD来识别药物的不良反应, 哪些对确保药品安全至关重要.

Q. RWD的局限性是什么?

A. RWD的使用存在一些挑战. 当我们将多个数字数据来源连接在一起时, 比如电子病历和保险索赔, 它会增加识别某人的风险, particularly if it involves a person with a rare disease and distinct demographics.

There is also the possibility of measurement errors because it’s not always clear that the data sources are measuring the concepts consistently. For example, 在健康记录中, a doctor may code a patient’s visit differently based on what the insurance company may cover, 哪一种会引起意义上的微妙变化.

Another limitation is that the data may not be representative of the population in general because in using EHRs, data are gathered from a population that is slightly sicker than the general population and a population who has access to health care, 排除那些不喜欢的人. Depending on the research question to be answered, these limitations can result in bias.

It’s also important to carefully assess the quality and completeness of the data. 在卫生保健设施收集的数据不一定具有可比性, 因为数据是不断变化的, 它们可能缺乏可重复性. However, 我们有评估质量和潜在偏倚的程序, 总的来说, 利大于弊.

Q. 趣赢平台如何使用RWD来支持客户?

A. 我们在很多项目中都使用了RWD. 其中包括red - iv - p、DAWN和VISION. 我们协调数据，以便将其转换为一个内聚的数据集. In REDS-IV-P, 一项研究将献血者, 组件的特点, 以及接受者的结果, 重点是儿科人群, 我们进行与输血医学实践和结果相关的分析. DAWN is a nationwide public health surveillance system designed to provide early warning and ongoing monitoring of emerging drug trends and characteristics of drug and/or alcohol-related emergency department visits. The RWD work allows the identification of drugs and drug combinations seen in ED visits nationwide. 对于VISION, 哪一个利用了现有的虚拟网络, 包括VISION流感网络, 我们整合了来自全美9个医疗系统的大量数据.S. The RWD from these systems are sent through a secure data pipeline where 趣赢平台 administers quality checks and performs analyses, 可以迅速向疾病控制中心报告.

Q. 趣赢平台如何在利用RWD方面与竞争对手区别开来?

A. We have the technologies to integrate data from multiple sources and the tools to map data to common data models. 我们有杰出的统计学家, 数据科学家, and epidemiologists who understand the sources of bias and can apply corrections to the data using techniques like weighting and imputation. Plus, we have subject matter experts deeply knowledgeable about a wide range of health outcomes. So, it is this comprehensive understanding of what’s needed to harness RWD to solve our clients challenges that distinguishes us from competitors.

Q. 你认为RWD的未来用途是什么?

A. 随着数据源的集成和数据的可用性的增加, I can foresee RWD being harnessed to increase our understanding of population and individual health, which will enable us to tailor medical interventions more precisely to the needs of individual patients. RWD的选择是多种多样的, and 趣赢平台 will continue to bring our diverse resources to address the challenges. 通过汇集流行病学方面的技能, statistics, data science, 和信息, 并且对健康结果有广泛的了解, 趣赢平台 is able to maximize the utility and quality of RWD and the real-world evidence it generates.