title: Automated data extraction: merging clinical care with real-time cohort-specific research and quality improvement data.
abstract: OBJECTIVE
  Although prohibitively labor intensive, manual data extraction (MDE) is the prevailing method used to obtain clinical research and quality improvement (QI) data. Automated data extraction (ADE) offers a powerful alternative. The purposes of this study were to 1) assess the feasibility of ADE from provider-authored outpatient documentation, and 2) evaluate the effectiveness of ADE compared to MDE.
  
  
  METHODS
  A prospective collection of data was performed on 90 ADE-templated notes (N=71 patients) evaluated in our bowel management clinic. ADE captured data were compared to 59 MDE notes (N=51) collected under an IRB-exempt review. Sixteen variables were directly comparable between ADE and MDE.
  
  
  RESULTS
  MDE for 59 clinic notes (27 unique variables) took 6months to complete. ADE-templated notes for 90 clinic notes (154 unique variables) took 5min to run a research/QI report. Implementation of ADE included eight weeks of development and testing. Pre-implementation clinical documentation was similar to post-implementation documentation (5-10min).
  
  
  CONCLUSIONS
  ADE-templated notes allow for a 5-fold increase in clinically relevant data that can be captured with each encounter. ADE also results in real-time data extraction to a research/QI database that is easily queried. The immediate availability of these data, in a research-formatted spreadsheet, allows for rapid collection, analyses, and interpretation of the data.
  
  
  METHODS
  IV.
  
  
  METHODS
  Retrospective Study.
authors.affiliation: Ann and Robert H. Lurie Children's Hospital of Chicago, Chicago, IL. Electronic address: fhebal@luriechildrens.org.
authors.forename: Ferdynand
authors.initials: F
authors.lastname: Hebal
authors.affiliation: Ann and Robert H. Lurie Children's Hospital of Chicago, Chicago, IL.
authors.forename: Elizabeth
authors.initials: E
authors.lastname: Nanney
authors.affiliation: Ann and Robert H. Lurie Children's Hospital of Chicago, Chicago, IL.
authors.forename: Christine
authors.initials: C
authors.lastname: Stake
authors.affiliation: Ann and Robert H. Lurie Children's Hospital of Chicago, Chicago, IL.
authors.forename: M L
authors.initials: ML
authors.lastname: Miller
authors.affiliation: Ann and Robert H. Lurie Children's Hospital of Chicago, Chicago, IL.
authors.forename: George
authors.initials: G
authors.lastname: Lales
authors.affiliation: Ann and Robert H. Lurie Children's Hospital of Chicago, Chicago, IL.
authors.forename: Katherine A
authors.initials: KA
authors.lastname: Barsness
mesh_terms: D000368:Aged; D035843:Biomedical Research; D004282:Documentation / Q000592:standards*; D001330:Electronic Data Processing / Q000592:standards*; D057286:Electronic Health Records; D006801:Humans; D008875:Middle Aged; D058996:Quality Improvement; D012189:Retrospective Studies
keywords: Automated data extraction; Clinical documentation; Electronic data capture; Electronic documentation; Templated notes