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哥伦比亚开放健康数据，来自电子健康记录的临床概念流行率和共同出现。

Columbia Open Health Data, clinical concept prevalence and co-occurrence from electronic health records.

机构信息

Department of Biomedical Informatics, Columbia University, NY, USA.

Institute of Data Science, Maastricht University, Maastricht, The Netherlands.

出版信息

Sci Data. 2018 Nov 27;5:180273. doi: 10.1038/sdata.2018.273.

DOI:10.1038/sdata.2018.273
PMID:30480666
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC6257042/
Abstract

Columbia Open Health Data (COHD) is a publicly accessible database of electronic health record (EHR) prevalence and co-occurrence frequencies between conditions, drugs, procedures, and demographics. COHD was derived from Columbia University Irving Medical Center's Observational Health Data Sciences and Informatics (OHDSI) database. The lifetime dataset, derived from all records, contains 36,578 single concepts (11,952 conditions, 12,334 drugs, and 10,816 procedures) and 32,788,901 concept pairs from 5,364,781 patients. The 5-year dataset, derived from records from 2013-2017, contains 29,964 single concepts (10,159 conditions, 10,264 drugs, and 8,270 procedures) and 15,927,195 concept pairs from 1,790,431 patients. Exclusion of rare concepts (count ≤ 10) and Poisson randomization enable data sharing by eliminating risks to patient privacy. EHR prevalences are informative of healthcare consumption rates. Analysis of co-occurrence frequencies via relative frequency analysis and observed-expected frequency ratio are informative of associations between clinical concepts, useful for biomedical research tasks such as drug repurposing and pharmacovigilance. COHD is publicly accessible through a web application-programming interface (API) and downloadable from the Figshare repository. The code is available on GitHub.

摘要

哥伦比亚开放健康数据 (COHD) 是一个公共可访问的电子健康记录 (EHR) 患病率和疾病、药物、程序和人口统计学之间共同出现频率的数据库。COHD 源自哥伦比亚大学欧文医学中心的观察性健康数据科学和信息学 (OHDSI) 数据库。来自所有记录的终生数据集包含 36,578 个单一概念（11,952 种疾病、12,334 种药物和 10,816 种程序）和 32,788,901 个来自 5,364,781 名患者的概念对。来自 2013-2017 年记录的 5 年数据集包含 29,964 个单一概念（10,159 种疾病、10,264 种药物和 8,270 种程序）和 15,927,195 个来自 1,790,431 名患者的概念对。排除罕见概念（计数 ≤ 10）和泊松随机化通过消除对患者隐私的风险来实现数据共享。EHR 患病率可用于了解医疗保健消费率。通过相对频率分析和观察到的预期频率比分析共同出现频率可用于分析临床概念之间的关联，这对于药物重新利用和药物警戒等生物医学研究任务很有用。COHD 通过 Web 应用程序编程接口 (API) 公开访问，并可从 Figshare 存储库下载。该代码可在 GitHub 上获得。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/bc95/6257042/3791fb3ff918/sdata2018273-f4.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/bc95/6257042/c8ea6a9a8b86/sdata2018273-f1.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/bc95/6257042/e4b76b367163/sdata2018273-f2.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/bc95/6257042/e40935915ed9/sdata2018273-f3.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/bc95/6257042/3791fb3ff918/sdata2018273-f4.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/bc95/6257042/c8ea6a9a8b86/sdata2018273-f1.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/bc95/6257042/e4b76b367163/sdata2018273-f2.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/bc95/6257042/e40935915ed9/sdata2018273-f3.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/bc95/6257042/3791fb3ff918/sdata2018273-f4.jpg

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