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流行病学问卷 (EPI-Q) - 一种可扩展的、基于应用程序的健康调查,与电子健康记录和基因型数据相关联。

Epidemiologic Questionnaire (EPI-Q) - a scalable, app-based health survey linked to electronic health record and genotype data.

机构信息

Department of Biostatistics, University of Michigan, Ann Arbor, MI, USA.

Center for Precision Health Data Science, University of Michigan, Ann Arbor, MI, USA.

出版信息

Epidemiol Health. 2023;45:e2023074. doi: 10.4178/epih.e2023074. Epub 2023 Aug 8.

DOI:10.4178/epih.e2023074
PMID:37591787
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC10867525/
Abstract

The Epidemiologic Questionnaire (EPI-Q) was established to collect broad, uniform, self-reported health data to supplement electronic health record (EHR) and genotype information from participants in the University of Michigan (UM) Precision Health cohorts. Recruitment of EPI-Q participants, who were already enrolled in 1 of 3 ongoing UM Precision Health cohorts-the Michigan Genomics Initiative, Mental Health Biobank, and Metabolism, Endocrinology, and Diabetes cohorts-began in March 2020. Of 54,043 retrospective invitations, 5,577 individuals enrolled, representing a 10.3% response rate. Of these, 3,502 (63.7%) were female, and the average age was 56.1 years (standard deviation, 15.4). The baseline survey comprises 11 modules on topics including personal and family health history, lifestyle, and cancer screening and history. Additionally, 11 optional modules cover topics including financial toxicity, occupational exposure, and life meaning. The questions are based on standardized and validated instruments used in other cohorts, and we share resources to expedite development of similar surveys. Data are collected via the MyDataHelps platform, which enables current and future participants to share non-Michigan Medicine EHR data. Recruitment is ongoing. Cohort data are available to those with institutional review board approval; for details, contact the Data Office for Clinical and Translational Research (DataOffice@umich.edu).

摘要

《流行病学问卷(EPI-Q)》的设立旨在收集广泛、统一、自我报告的健康数据,以补充密歇根大学(UM)精准健康队列参与者的电子健康记录(EHR)和基因型信息。EPI-Q 参与者的招募工作已于 2020 年 3 月开始,这些参与者已经参加了 UM 精准健康队列中的 3 个队列之一:密歇根基因组计划、心理健康生物库和代谢、内分泌和糖尿病队列。在 54043 份回顾性邀请中,有 5577 人注册,回应率为 10.3%。其中,3502 人(63.7%)为女性,平均年龄为 56.1 岁(标准差为 15.4)。基线调查包括 11 个模块,涵盖个人和家族健康史、生活方式以及癌症筛查和病史等主题。此外,还有 11 个可选模块涵盖财务毒性、职业暴露和生活意义等主题。这些问题基于其他队列中使用的标准化和经过验证的工具,我们共享资源以加快类似调查的开发。数据通过 MyDataHelps 平台收集,该平台使现有和未来的参与者能够共享非密歇根医学 EHR 数据。招募工作正在进行中。队列数据可供具有机构审查委员会批准的人员使用;有关详细信息,请联系临床和转化研究数据办公室(DataOffice@umich.edu)。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2e72/10867525/8aa9c58dd2f9/epih-45-e2023074f3.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2e72/10867525/7ca5b2bf831b/epih-45-e2023074f1.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2e72/10867525/5c58b9f33ccd/epih-45-e2023074f2.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2e72/10867525/8aa9c58dd2f9/epih-45-e2023074f3.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2e72/10867525/7ca5b2bf831b/epih-45-e2023074f1.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2e72/10867525/5c58b9f33ccd/epih-45-e2023074f2.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2e72/10867525/8aa9c58dd2f9/epih-45-e2023074f3.jpg

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本文引用的文献

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Cell Genom. 2023 Jan 31;3(2):100257. doi: 10.1016/j.xgen.2023.100257. eCollection 2023 Feb 8.
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Measurement and Validation of the Comprehensive Score for Financial Toxicity (COST) in a Population With Diabetes.测量和验证糖尿病患者的综合财务毒性评分(COST)。
Diabetes Care. 2022 Nov 1;45(11):2535-2543. doi: 10.2337/dc22-0494.
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Predicting persistent opioid use after surgery using electronic health record and patient-reported data.
利用电子健康记录和患者报告数据预测手术后持续使用阿片类药物。
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A roadmap to increase diversity in genomic studies.增加基因组研究多样性的路线图。
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Associations Between Satisfaction With Aging and Health and Well-being Outcomes Among Older US Adults.美国老年人中对衰老的满意度与健康和幸福结果之间的关联。
JAMA Netw Open. 2022 Feb 1;5(2):e2147797. doi: 10.1001/jamanetworkopen.2021.47797.
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Lack of Arab or Middle Eastern and North African Health Data Undermines Assessment of Health Disparities.缺乏阿拉伯、中东和北非地区的健康数据会影响对健康差异的评估。
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