克服健康研究中个人购物史数据的偏差

IF 12.4 1区 医学 Q1 HEALTH CARE SCIENCES & SERVICES
Anya Skatova
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引用次数: 0

摘要

人口数据的新来源,特别是行政和医疗记录,以及通过与在线服务互动产生的数字足迹,为推进健康研究和决策提供了大量机会。购物历史记录就是一个很好的例子,它可以通过仔细研究现实世界中的大量日常选择来揭示人口健康的方方面面。然而,与任何数据集一样,这些数据源也有特定的局限性,包括抽样偏差、有效性问题和测量误差。为了提高购物数据在健康研究中的适用性和潜力,我们主张将个人层面的购物数据与包含丰富的纵向人群队列研究资料库的外部数据集进行整合。这种战略方法有望设计出创新的方法来解决固有的数据局限性和偏差。通过仔细记录偏差、建立经过验证的关联以及在这些合并记录中找出模式,研究人员可以将他们的研究结果推广到来自全国连锁超市的全人口数据集。将人口健康数据与现实世界中有关食品、饮料和非处方药(如止痛药)的选择进行验证和联系,为了解这些选择及其相关行为模式对公众健康的影响提供了一个重要机会。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Overcoming biases of individual level shopping history data in health research
Novel sources of population data, especially administrative and medical records, as well as the digital footprints generated through interactions with online services, present a considerable opportunity for advancing health research and policymaking. An illustrative example is shopping history records that can illuminate aspects of population health by scrutinizing extensive sets of everyday choices made in the real world. However, like any dataset, these sources possess specific limitations, including sampling biases, validity issues, and measurement errors. To enhance the applicability and potential of shopping data in health research, we advocate for the integration of individual-level shopping data with external datasets containing rich repositories of longitudinal population cohort studies. This strategic approach holds the promise of devising innovative methodologies to address inherent data limitations and biases. By meticulously documenting biases, establishing validated associations, and discerning patterns within these amalgamated records, researchers can extrapolate their findings to encompass population-wide datasets derived from national supermarket chain. The validation and linkage of population health data with real-world choices pertaining to food, beverages, and over-the-counter medications, such as pain relief, present a significant opportunity to comprehend the impact of these choices and behavioural patterns associated with them on public health.
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来源期刊
CiteScore
25.10
自引率
3.30%
发文量
170
审稿时长
15 weeks
期刊介绍: npj Digital Medicine is an online open-access journal that focuses on publishing peer-reviewed research in the field of digital medicine. The journal covers various aspects of digital medicine, including the application and implementation of digital and mobile technologies in clinical settings, virtual healthcare, and the use of artificial intelligence and informatics. The primary goal of the journal is to support innovation and the advancement of healthcare through the integration of new digital and mobile technologies. When determining if a manuscript is suitable for publication, the journal considers four important criteria: novelty, clinical relevance, scientific rigor, and digital innovation.
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