title: Data for free--can an electronic medical record provide outcome data for incontinence/prolapse repair procedures?
abstract: OBJECTIVE
  We determined whether a custom computer program can improve the extraction and accuracy of key outcome measures from progress notes in an electronic medical record compared to a traditional data recording system for incontinence and prolapse repair procedures.
  
  
  METHODS
  Following institutional review board approval, progress notes were exported from the Epic electronic medical record system for outcome measure extraction by a custom computer program. The extracted data (D1) were compared against a manually maintained outcome measures database (D2). This work took place in 2 phases. During the first phase, volatile data such as questionnaires and standardized physical examination findings using the POP-Q (pelvic organ prolapse quantification) system were extracted from existing progress notes. The second phase used a progress note template incorporating key outcome measures to evaluate improvement in data accuracy and extraction rates.
  
  
  RESULTS
  Phase 1 compared 6,625 individual outcome measures from 316 patients in D2 to 3,534 outcome measures extracted from progress notes in D1, resulting in an extraction rate of 53.3%. A subset of 3,763 outcome measures from D1 was created by excluding data that did not exist in the extraction, yielding an accuracy rate of 93.9%. With the use of the template in phase 2, the extraction rate improved to 91.9% (273 of 297) and the accuracy rate improved to 100% (273 of 273).
  
  
  CONCLUSIONS
  In the field of incontinence and prolapse, the disciplined use of an electronic medical record template containing a preestablished set of key outcome measures can provide the ideal interface between required documentation and clinical research.
authors.affiliation: Department of Urology, University of Texas Southwestern Medical Center, Dallas, Texas 75390-9110, USA. Matthew.Steidl@utsouthwestern.edu
authors.forename: Matthew
authors.initials: M
authors.lastname: Steidl
authors.forename: Philippe
authors.initials: P
authors.lastname: Zimmern
mesh_terms: D057225:Data Mining; D057286:Electronic Health Records; D005260:Female; D006801:Humans; D017063:Outcome Assessment, Health Care / Q000379:methods*; D056887:Pelvic Organ Prolapse / Q000601:surgery*; D011996:Records; D014549:Urinary Incontinence / Q000601:surgery*