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. 2013 Jan 1;20(1):117-21.
doi: 10.1136/amiajnl-2012-001145. Epub 2012 Sep 6.

Next-generation phenotyping of electronic health records

George Hripcsak  1 , David J Albers
Affiliations

Next-generation phenotyping of electronic health records

George Hripcsak et al. J Am Med Inform Assoc. .

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.

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Figures

Figure 1
Figure 1
Feedback loops in the electronic health record. The state of the patient varies, and it determines not only the value of the measurements in the record, but also the type and timing of the measurements.
Figure 2
Figure 2
Phenotyping and discovery. The raw electronic health record (EHR) data are an indirect reflection of the true patient state due to the recording process. Attempts to create phenotypes and discover knowledge must account for the recording. The healthcare process model represents the salient features of the recording process and informs the phenotyping and discovery.
See this image and copyright information in PMC

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