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利用国家新冠队列协作组评估新冠病毒检测中的差异。

Assessing Disparities in COVID-19 Testing Using National COVID Cohort Collaborative.

作者信息

Lyu Jinyan, Cui Wanting, Finkelstein Joseph

机构信息

Icahn School of Medicine at Mount Sinai, New York NY, USA.

出版信息

Stud Health Technol Inform. 2022 Jun 29;295:316-319. doi: 10.3233/SHTI220726.

Abstract

With NCATS National COVID Cohort Collaborative (N3C) dataset, we evaluated 14 billion medical records and identified more than 12 million patients tested for COVID-19 across the US. To assess potential disparities in COVID-19 testing, we chose ten US states and then compared each state's population distribution characteristics with distribution of corresponding characteristics from N3C. Minority racial groups were more prevalent in the N3C dataset as compared to census data. The proportion of Hispanics and Latinos in N3C was slightly lower than in the state census. Patients over 65 years old had higher representation in the N3C dataset and patients under 18 were underrepresented. Proportion of females in the N3C was higher compared with the state data. All ten states in N3C showed a higher representation of urban population versus rural population compared to census data.

摘要

利用美国国立转化医学推进中心(NCATS)的全国新冠队列协作项目(N3C)数据集,我们评估了140亿份医疗记录,并识别出全美超过1200万名接受过新冠病毒检测的患者。为评估新冠病毒检测中可能存在的差异,我们选取了美国十个州,然后将每个州的人口分布特征与N3C相应特征的分布进行比较。与人口普查数据相比,少数族裔群体在N3C数据集中更为普遍。N3C中西班牙裔和拉丁裔的比例略低于州人口普查数据。65岁以上的患者在N3C数据集中的占比更高,而18岁以下的患者占比不足。N3C中女性的比例高于州数据。与人口普查数据相比,N3C中的所有十个州城市人口的占比均高于农村人口。

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