Send to

Choose Destination
AMIA Jt Summits Transl Sci Proc. 2017 Jul 26;2017:512-521. eCollection 2017.

Eye-tracking for clinical decision support: A method to capture automatically what physicians are viewing in the EMR.

Author information

Department of Biomedical Informatics, University of Pittsburgh, Pittsburgh, PA, USA.
Intelligent Systems Program, University of Pittsburgh, Pittsburgh, PA, USA.
Department of Critical Care Medicine, University of Pittsburgh, Pittsburgh, PA, USA.


Eye-tracking is a valuable research tool that is used in laboratory and limited field environments. We take steps toward developing methods that enable widespread adoption of eye-tracking and its real-time application in clinical decision support. Eye-tracking will enhance awareness and enable intelligent views, more precise alerts, and other forms of decision support in the Electronic Medical Record (EMR). We evaluated a low-cost eye-tracking device and found the device's accuracy to be non-inferior to a more expensive device. We also developed and evaluated an automatic method for mapping eye-tracking data to interface elements in the EMR (e.g., a displayed laboratory test value). Mapping was 88% accurate across the six participants in our experiment. Finally, we piloted the use of the low-cost device and the automatic mapping method to label training data for a Learning EMR (LEMR) which is a system that highlights the EMR elements a physician is predicted to use.


Supplemental Content

Full text links

Icon for PubMed Central
Loading ...
Support Center