Breen Nancy, Berrigan David, Jackson James S, Wong David W S, Wood Frederick B, Denny Joshua C, Zhang Xinzhi, Bourne Philip E
National Institute on Minority Health and Health Disparities, National Institutes of Health, Bethesda, Maryland.
Division of Cancer Control and Population Sciences, National Cancer Institute, Bethesda, Maryland.
Health Equity. 2019 Nov 8;3(1):588-600. doi: 10.1089/heq.2019.0042. eCollection 2019.
Despite decades of research and interventions, significant health disparities persist. Seventeen years is the estimated time to translate scientific discoveries into public health action. This Narrative Review argues that the translation process could be accelerated if representative data were gathered and used in more innovative and efficient ways. The National Institute on Minority Health and Health Disparities led a multiyear visioning process to identify research opportunities designed to frame the next decade of research and actions to improve minority health and reduce health disparities. "Big data" was identified as a research opportunity and experts collaborated on a systematic vision of how to use big data both to improve the granularity of information for place-based study and to efficiently translate health disparities research into improved population health. This Narrative Review is the result of that collaboration. Big data could enhance the process of translating scientific findings into reduced health disparities by contributing information at fine spatial and temporal scales suited to interventions. In addition, big data could fill pressing needs for health care system, genomic, and social determinant data to understand mechanisms. Finally, big data could lead to appropriately personalized health care for demographic groups. Rich new resources, including social media, electronic health records, sensor information from digital devices, and crowd-sourced and citizen-collected data, have the potential to complement more traditional data from health surveys, administrative data, and investigator-initiated registries or cohorts. This Narrative Review argues for a renewed focus on translational research cycles to accomplish this continual assessment. The promise of big data extends from etiology research to the evaluation of large-scale interventions and offers the opportunity to accelerate translation of health disparities studies. This data-rich world for health disparities research, however, will require continual assessment for efficacy, ethical rigor, and potential algorithmic or system bias.
尽管经过了数十年的研究和干预，重大的健康差距依然存在。将科学发现转化为公共卫生行动预计需要17年时间。本叙述性综述认为，如果以更具创新性和高效性的方式收集和使用代表性数据，转化过程可以加速。美国国立少数族裔健康与健康差异研究所主导了一个为期多年的构想过程，以确定旨在规划未来十年研究和行动的研究机会，以改善少数族裔健康并减少健康差距。“大数据”被确定为一个研究机会，专家们就如何利用大数据提高基于地点研究的信息粒度以及如何有效地将健康差距研究转化为改善人群健康进行了系统构想。本叙述性综述就是该合作的成果。大数据可以通过在适合干预的精细时空尺度上提供信息，来加强将科学发现转化为减少健康差距的过程。此外，大数据可以满足对医疗保健系统、基因组和社会决定因素数据的迫切需求，以了解相关机制。最后，大数据可以为不同人群带来适当的个性化医疗保健。丰富的新资源，包括社交媒体、电子健康记录、数字设备的传感器信息以及众包和公民收集的数据，有可能补充来自健康调查、行政数据以及研究者发起的登记册或队列的更传统数据。本叙述性综述主张重新关注转化研究周期，以完成这种持续评估。大数据的前景从病因学研究延伸到大规模干预的评估，并提供了加速健康差距研究转化的机会。然而，这个数据丰富的健康差距研究世界将需要对有效性、伦理严谨性以及潜在的算法或系统偏差进行持续评估。
