Next-generation phenotyping of electronic health records.
Where this comes from
- Record sourced from PubMed, PMID 22955496.
- Also identified by DOI 10.1136/amiajnl-2012-001145 and PMC identifier 3555337.
- Licence recorded as CC BY-NC.
- Because redistribution is not established, this page shows the abstract only. Follow the links below for the full text.
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.
Medical subject headings
- Data Mining
- Diffusion of Innovation
- Electronic Health Records