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Enhanced identification of eligibility for depression research using an electronic medical record search engine
Lisa Seyfried1, David A Hanauer, Donald Nease
1Department of Psychiatry, University of Michigan Medical School, Ann Arbor, MI 48109, USA.
Purpose:
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.
