A comparison of two approaches to text processing: facilitating chart reviews of radiology reports in electronic medical records

Perspect Health Inf Manag. 2010 Oct 1;7(Fall):1a.

Abstract

Chart review is central to health services research. Text processing, which analyzes free-text fields through automated methods, can facilitate this process. We compared precision and accuracy of NegEx and SQLServer 2008 Free-Text Search in identifying acute fractures in radiology reports.The term "fracture" was included in 23,595 radiology reports from the Veterans Aging Cohort Study. Four hundred reports were randomly selected and manually reviewed for acute fractures to establish a gold standard. Reports were then processed by SQLServer and NegEx. Results were compared to the gold standard to determine accuracy, precision, recall, and F-statistic.NegEx and the gold standard identified acute fractures in 13 reports. SQLServer identified 2 in a report-based analysis (precision: 1.00; accuracy: 0.97; recall: 0.15; F-statistic: 0.26), and 12 in a sentence-by-sentence analysis (precision: 1.00; recall: 0.92; accuracy: 0.92; F-statistic: 0.96).Text-processing tools utilizing basic database or programming skills are comparable, precise, and accurate in identifying reports for review.

Publication types

  • Comparative Study
  • Research Support, N.I.H., Extramural
  • Research Support, Non-U.S. Gov't
  • Research Support, U.S. Gov't, Non-P.H.S.

MeSH terms

  • Algorithms
  • Cohort Studies
  • Electronic Health Records*
  • False Negative Reactions
  • Fractures, Bone / diagnostic imaging
  • Health Services Research
  • Humans
  • Information Storage and Retrieval / standards*
  • Medical Audit / methods*
  • Natural Language Processing*
  • Radiography
  • Radiology Department, Hospital*
  • Sensitivity and Specificity
  • United States