{"title":"利用 \"我们所有人 \"数据库的大型数据集开展初级保健研究。","authors":"Daniel J Parente","doi":"10.3122/jabfm.2023.230453R2","DOIUrl":null,"url":null,"abstract":"<p><p>The National Institutes of Health (NIH) are supporting the <i>All of Us</i> research program, a large multicenter initiative to accelerate precision medicine. The <i>All of Us</i> database contains information on greater than 400,000 individuals spanning thousands of medical conditions, drug exposure types, and laboratory test types. These data can be correlated with genomic information and with survey data on social and environmental factors which influence health. A core principle of the <i>All of Us</i> program is that participants should reflect the diversity present in the United States population.The <i>All of Us</i> database has advanced many areas of medicine but is currently underutilized by primary care and public health researchers. In this Special Communication article, I seek to reduce the \"barrier to entry\" for primary care researchers to develop new projects within the <i>All of Us</i> Researcher Workbench. This Special Communication discusses (1) obtaining access to the database, (2) using the database securely and responsibly, (3) the key design concepts of the Researcher Workbench, and (4) details of data set extraction and analysis in the cloud computing environment. Fully documented, tutorial R statistical programming language and Python programs are provided alongside this article, which researchers may freely adapt under the open-source MIT license. The primary care research community should use the <i>All of Us</i> database to accelerate innovation in primary care research, make epidemiologic discoveries, promote community health, and further the infrastructure-building strategic priority of the family medicine 2024 to 2030 National Research Strategy.</p>","PeriodicalId":50018,"journal":{"name":"Journal of the American Board of Family Medicine","volume":" ","pages":""},"PeriodicalIF":2.4000,"publicationDate":"2024-11-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Leveraging the All of Us Database for Primary Care Research with Large Datasets.\",\"authors\":\"Daniel J Parente\",\"doi\":\"10.3122/jabfm.2023.230453R2\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><p>The National Institutes of Health (NIH) are supporting the <i>All of Us</i> research program, a large multicenter initiative to accelerate precision medicine. The <i>All of Us</i> database contains information on greater than 400,000 individuals spanning thousands of medical conditions, drug exposure types, and laboratory test types. These data can be correlated with genomic information and with survey data on social and environmental factors which influence health. A core principle of the <i>All of Us</i> program is that participants should reflect the diversity present in the United States population.The <i>All of Us</i> database has advanced many areas of medicine but is currently underutilized by primary care and public health researchers. In this Special Communication article, I seek to reduce the \\\"barrier to entry\\\" for primary care researchers to develop new projects within the <i>All of Us</i> Researcher Workbench. This Special Communication discusses (1) obtaining access to the database, (2) using the database securely and responsibly, (3) the key design concepts of the Researcher Workbench, and (4) details of data set extraction and analysis in the cloud computing environment. Fully documented, tutorial R statistical programming language and Python programs are provided alongside this article, which researchers may freely adapt under the open-source MIT license. The primary care research community should use the <i>All of Us</i> database to accelerate innovation in primary care research, make epidemiologic discoveries, promote community health, and further the infrastructure-building strategic priority of the family medicine 2024 to 2030 National Research Strategy.</p>\",\"PeriodicalId\":50018,\"journal\":{\"name\":\"Journal of the American Board of Family Medicine\",\"volume\":\" \",\"pages\":\"\"},\"PeriodicalIF\":2.4000,\"publicationDate\":\"2024-11-15\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Journal of the American Board of Family Medicine\",\"FirstCategoryId\":\"3\",\"ListUrlMain\":\"https://doi.org/10.3122/jabfm.2023.230453R2\",\"RegionNum\":3,\"RegionCategory\":\"医学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q1\",\"JCRName\":\"MEDICINE, GENERAL & INTERNAL\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of the American Board of Family Medicine","FirstCategoryId":"3","ListUrlMain":"https://doi.org/10.3122/jabfm.2023.230453R2","RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"MEDICINE, GENERAL & INTERNAL","Score":null,"Total":0}
引用次数: 0
摘要
美国国立卫生研究院(NIH)正在支持 "我们所有人"(All of Us)研究计划,这是一项旨在加速精准医疗的大型多中心计划。我们所有人 "数据库包含 40 多万人的信息,涉及数千种医疗条件、药物接触类型和实验室测试类型。这些数据可与基因组信息以及影响健康的社会和环境因素调查数据相关联。我们所有人 "计划的核心原则是,参与者应反映美国人口的多样性。"我们所有人 "数据库推动了许多医学领域的发展,但目前初级保健和公共卫生研究人员对其利用不足。在这篇特别通讯文章中,我试图降低初级保健研究人员在 "我们所有人 "研究人员工作台中开发新项目的 "准入门槛"。这篇特别通讯讨论了:(1)获取数据库访问权;(2)安全、负责任地使用数据库;(3)研究人员工作台的关键设计理念;(4)在云计算环境中提取和分析数据集的细节。本文还提供了文档齐全的 R 统计编程语言教程和 Python 程序,研究人员可根据开源 MIT 许可自由改编。全科研究界应利用 "我们所有人 "数据库加快全科研究的创新,取得流行病学发现,促进社区健康,并推进《家庭医学 2024 至 2030 年国家研究战略》的基础设施建设战略重点。
Leveraging the All of Us Database for Primary Care Research with Large Datasets.
The National Institutes of Health (NIH) are supporting the All of Us research program, a large multicenter initiative to accelerate precision medicine. The All of Us database contains information on greater than 400,000 individuals spanning thousands of medical conditions, drug exposure types, and laboratory test types. These data can be correlated with genomic information and with survey data on social and environmental factors which influence health. A core principle of the All of Us program is that participants should reflect the diversity present in the United States population.The All of Us database has advanced many areas of medicine but is currently underutilized by primary care and public health researchers. In this Special Communication article, I seek to reduce the "barrier to entry" for primary care researchers to develop new projects within the All of Us Researcher Workbench. This Special Communication discusses (1) obtaining access to the database, (2) using the database securely and responsibly, (3) the key design concepts of the Researcher Workbench, and (4) details of data set extraction and analysis in the cloud computing environment. Fully documented, tutorial R statistical programming language and Python programs are provided alongside this article, which researchers may freely adapt under the open-source MIT license. The primary care research community should use the All of Us database to accelerate innovation in primary care research, make epidemiologic discoveries, promote community health, and further the infrastructure-building strategic priority of the family medicine 2024 to 2030 National Research Strategy.
期刊介绍:
Published since 1988, the Journal of the American Board of Family Medicine ( JABFM ) is the official peer-reviewed journal of the American Board of Family Medicine (ABFM). Believing that the public and scientific communities are best served by open access to information, JABFM makes its articles available free of charge and without registration at www.jabfm.org. JABFM is indexed by Medline, Index Medicus, and other services.