Abstract
Puya is a method that compares the physical exam in an electronic clinical note with a set of stereotypical physical exam sentences that have been previously classified as "normal". The note is then displayed in a web browser with normal findings clearly delineated. The list of stereotypical sentences comes from a set of physical findings found within extensive electronic medical record. This list is then screened to select only those that represent "normal" findings, a process that yields 96% total agreement among 4 clinicians surveyed. This final list of stereotypical "normal" sentences accounts for 64% of the clinical narrative text. Sentences in the clinical note that do not match sentences in the "normal" list are assumed to be "abnormal". Puya screened 98 clinical notes consisting of 610 individual sentences. Puya achieved a sensitivity of 100%, a specificity of 63%, a positive predictive value of 44% and a negative predictive value of 100%. This leads to an application that reduces informational noise.
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Selected References
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- Hersh W. R., Campbell E. H., Evans D. A., Brownlow N. D. Empirical, automated vocabulary discovery using large text corpora and advanced natural language processing tools. Proc AMIA Annu Fall Symp. 1996:159–163. [PMC free article] [PubMed] [Google Scholar]
- Murphy S. N., Barnett G. O. Achieving automated narrative text interpretation using phrases in the electronic medical record. Proc AMIA Annu Fall Symp. 1996:532–536. [PMC free article] [PubMed] [Google Scholar]
- Sager N., Lyman M., Bucknall C., Nhan N., Tick L. J. Natural language processing and the representation of clinical data. J Am Med Inform Assoc. 1994 Mar-Apr;1(2):142–160. doi: 10.1136/jamia.1994.95236145. [DOI] [PMC free article] [PubMed] [Google Scholar]
- Sager N., Nhàn N. T., Lyman M., Tick L. J. Medical language processing with SGML display. Proc AMIA Annu Fall Symp. 1996:547–551. [PMC free article] [PubMed] [Google Scholar]
- Spackman K. A., Hersh W. R. Recognizing noun phrases in medical discharge summaries: an evaluation of two natural language parsers. Proc AMIA Annu Fall Symp. 1996:155–158. [PMC free article] [PubMed] [Google Scholar]