title: Enhanced identification of eligibility for depression research using an electronic medical record search engine.
abstract: 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.
authors: Department of Psychiatry, University of Michigan Medical School, Ann Arbor, MI 48109, USA.
authors: Lisa
authors: L
authors: Seyfried
authors: David A
authors: DA
authors: Hanauer
authors: Donald
authors: D
authors: Nease
authors: Rashad
authors: R
authors: Albeiruti
authors: Janet
authors: J
authors: Kavanagh
authors: Helen C
authors: HC
authors: Kales
mesh_terms: 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