TY - JOUR
T1 - A comparison of two approaches to text processing
T2 - facilitating chart reviews of radiology reports in electronic medical records.
AU - Womack, Julie A.
AU - Scotch, Matthew
AU - Gibert, Cynthia
AU - Chapman, Wendy
AU - Yin, Michael
AU - Justice, Amy C.
AU - Brandt, Cynthia
N1 - Copyright:
This record is sourced from MEDLINE®/PubMed®, a database of the U.S. National Library of Medicine
PY - 2010
Y1 - 2010
N2 - 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.
AB - 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.
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M3 - Article
C2 - 21063542
AN - SCOPUS:79952794925
SN - 1559-4122
VL - 7
SP - 1a
JO - Perspectives in health information management / AHIMA, American Health Information Management Association
JF - Perspectives in health information management / AHIMA, American Health Information Management Association
ER -