Enhanced identification of eligibility for depression research using an electronic medical record search engine.
OBJECTIVE
Electronic medical records (EMRs) have become part of daily practice for many physicians. Attempts have been made to apply electronic search engine technology to speed EMR review. This was a prospective, observational study to compare the speed and clinical accuracy of a medical record search engine vs. manual review of the EMR.


METHODS
Three raters reviewed 49 cases in the EMR to screen for eligibility in a depression study using the electronic medical record search engine (EMERSE). One week later raters received a scrambled set of the same patients including 9 distractor cases, and used manual EMR review to determine eligibility. For both methods, accuracy was assessed for the original 49 cases by comparison with a gold standard rater.


RESULTS
Use of EMERSE resulted in considerable time savings; chart reviews using EMERSE were significantly faster than traditional manual review (p=0.03). The percent agreement of raters with the gold standard (e.g. concurrent validity) using either EMERSE or manual review was not significantly different.


CONCLUSIONS
Using a search engine optimized for finding clinical information in the free-text sections of the EMR can provide significant time savings while preserving clinical accuracy. The major power of this search engine is not from a more advanced and sophisticated search algorithm, but rather from a user interface designed explicitly to help users search the entire medical record in a way that protects health information.
Seyfried
Lisa
L
Department of Psychiatry, University of Michigan Medical School, Ann Arbor, MI 48109, USA.
Hanauer
David A
DA
Nease
Donald
D
Albeiruti
Rashad
R
Kavanagh
Janet
J
Kales
Helen C
HC
D035843:Biomedical Research / Q000379:methods*; D003657:Decision Making; D003863:Depression / Q000175:diagnosis*; D057286:Electronic Health Records; D006801:Humans; D016347:Medical Records Systems, Computerized; D008875:Middle Aged; D011446:Prospective Studies; D057386:Search Engine