Next-generation phenotyping of electronic health records. Hripcsak, G. & Albers, D. J. Journal of the American Medical Informatics Association: JAMIA, 20(1):117–121, January, 2013.
doi  abstract   bibtex   
The national adoption of electronic health records (EHR) promises to make an unprecedented amount of data available for clinical research, but the data are complex, inaccurate, and frequently missing, and the record reflects complex processes aside from the patient's physiological state. We believe that the path forward requires studying the EHR as an object of interest in itself, and that new models, learning from data, and collaboration will lead to efficient use of the valuable information currently locked in health records.
@article{hripcsak_next-generation_2013,
	title = {Next-generation phenotyping of electronic health records},
	volume = {20},
	issn = {1527-974X},
	doi = {10.1136/amiajnl-2012-001145},
	abstract = {The national adoption of electronic health records (EHR) promises to make an unprecedented amount of data available for clinical research, but the data are complex, inaccurate, and frequently missing, and the record reflects complex processes aside from the patient's physiological state. We believe that the path forward requires studying the EHR as an object of interest in itself, and that new models, learning from data, and collaboration will lead to efficient use of the valuable information currently locked in health records.},
	language = {eng},
	number = {1},
	journal = {Journal of the American Medical Informatics Association: JAMIA},
	author = {Hripcsak, George and Albers, David J.},
	month = jan,
	year = {2013},
	pmid = {22955496},
	pmcid = {PMC3555337},
	keywords = {Biomedical Research, Data Mining, Diffusion of Innovation, Electronic Health Records, Humans, Models, Theoretical, Quality Control, United States},
	pages = {117--121},
}

Downloads: 0