Curating and Integrating Data from Multiple Sources to Support Healthcare Analytics

被引：4

作者：

Ng, Kenney ^{[1
]}

Kakkanatt, Chris ^{[2
]}

Benigno, Michael ^{[2
]}

Thompson, Clay ^{[2
]}

Jackson, Margaret ^{[2
]}

Cahan, Amos ^{[1
]}

Zhu, Xinxin ^{[1
]}

Zhang, Ping ^{[1
]}

Huang, Paul ^{[3
,4
]}

机构：

[1] IBM TJ Watson Res Ctr, Yorktown Hts, NY USA

[2] Pfizer Inc, New York, NY USA

[3] Massachusetts Gen Hosp, Boston, MA 02114 USA

[4] Harvard Med Sch, Boston, MA USA

来源：

MEDINFO 2015: EHEALTH-ENABLED HEALTH | 2015年 / 216卷

关键词：

Data Collection; Data Curation; Automatic Data Processing;

D O I：

10.3233/978-1-61499-564-7-1056

中图分类号：

TP39 [计算机的应用];

学科分类号：

081203 ; 0835 ;

摘要：

As the volume and variety of healthcare related data continues to grow, the analysis and use of this data will increasingly depend on the ability to appropriately collect, curate and integrate disparate data from many different sources. We describe our approach to and highlight our experiences with the development of a robust data collection, curation and integration infrastructure that supports healthcare analytics. This system has been successfully applied to the processing of a variety of data types including clinical data from electronic health records and observational studies, genomic data, microbiomic data, self-reported data from surveys and self-tracked data from wearable devices from over 600 subjects. The curated data is currently being used to support healthcare analytic applications such as data visualization, patient stratification and predictive modeling.

引用

页码：1056 / 1056

页数：1