Automated data extraction: merging clinical care with real-time cohort-specific research and quality improvement data

Ferdynand Hebal*, Elizabeth Nanney, Christine Stake, M. L. Miller, George Lales, Katherine A. Barsness

*Corresponding author for this work

Research output: Contribution to journalArticle

4 Scopus citations

Abstract

Background/Purpose 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 6 months to complete. ADE-templated notes for 90 clinic notes (154 unique variables) took 5 min 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 (5–10 min). 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. Level of evidence IV. Type of study Retrospective Study.

Original languageEnglish (US)
Pages (from-to)149-152
Number of pages4
JournalJournal of pediatric surgery
Volume52
Issue number1
DOIs
StatePublished - Jan 1 2017

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Keywords

  • Automated data extraction
  • Clinical documentation
  • Electronic data capture
  • Electronic documentation
  • Templated notes

ASJC Scopus subject areas

  • Surgery
  • Pediatrics, Perinatology, and Child Health

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