Title |
Report of the National Heart, Lung, and Blood Institute Working Group
|
---|---|
Published in |
Circulation, April 2016
|
DOI | 10.1161/circulationaha.115.019506 |
Pubmed ID | |
Authors |
Sara K Pasquali, Jeffrey P Jacobs, Gregory K Farber, David Bertoch, Elizabeth D Blume, Kristin M Burns, Robert Campbell, Anthony C Chang, Wendy K Chung, Tiffany Riehle-Colarusso, Lesley H Curtis, Christopher B Forrest, William J Gaynor, Michael G Gaies, Alan S Go, Paul Henchey, Gerard R Martin, Gail Pearson, Victoria L Pemberton, Steven M Schwartz, Robert Vincent, Jonathan R Kaltman |
Abstract |
The National Heart, Lung, and Blood Institute convened a working group in January 2015 to explore issues related to an integrated data network for congenital heart disease research. The overall goal was to develop a common vision for how the rapidly increasing volumes of data captured across numerous sources can be managed, integrated, and analyzed to improve care and outcomes. This report summarizes the current landscape of congenital heart disease data, data integration methodologies used across other fields, key considerations for data integration models in congenital heart disease, and the short- and long-term vision and recommendations made by the working group. |
X Demographics
Geographical breakdown
Country | Count | As % |
---|---|---|
United States | 3 | 30% |
Netherlands | 1 | 10% |
Unknown | 6 | 60% |
Demographic breakdown
Type | Count | As % |
---|---|---|
Members of the public | 8 | 80% |
Scientists | 1 | 10% |
Practitioners (doctors, other healthcare professionals) | 1 | 10% |
Mendeley readers
Geographical breakdown
Country | Count | As % |
---|---|---|
Unknown | 60 | 100% |
Demographic breakdown
Readers by professional status | Count | As % |
---|---|---|
Researcher | 8 | 13% |
Student > Master | 7 | 12% |
Student > Bachelor | 7 | 12% |
Student > Ph. D. Student | 5 | 8% |
Professor | 4 | 7% |
Other | 15 | 25% |
Unknown | 14 | 23% |
Readers by discipline | Count | As % |
---|---|---|
Medicine and Dentistry | 20 | 33% |
Computer Science | 5 | 8% |
Psychology | 3 | 5% |
Nursing and Health Professions | 3 | 5% |
Engineering | 2 | 3% |
Other | 7 | 12% |
Unknown | 20 | 33% |