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01000naa a22002652 4500 |
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NLM104963522 |
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DE-627 |
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20231222133638.0 |
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tu |
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231222s1999 xx ||||| 00| ||eng c |
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|a DE-627
|b ger
|c DE-627
|e rakwb
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| 041 |
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|a eng
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| 100 |
1 |
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|a Friedman, C
|e verfasserin
|4 aut
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| 245 |
1 |
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|a Automating a severity score guideline for community-acquired pneumonia employing medical language processing of discharge summaries
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| 264 |
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|c 1999
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| 336 |
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|a Text
|b txt
|2 rdacontent
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| 337 |
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|a ohne Hilfsmittel zu benutzen
|b n
|2 rdamedia
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| 338 |
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|a Band
|b nc
|2 rdacarrier
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| 500 |
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|a Date Completed 01.02.2000
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| 500 |
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|a Date Revised 13.11.2018
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|a published: Print
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|a Citation Status MEDLINE
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| 520 |
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|a Obtaining encoded variables is often a key obstacle to automating clinical guidelines. Frequently the pertinent information occurs as text in patient reports, but text is inadequate for the task. This paper describes a retrospective study that automates determination of severity classes for patients with community-acquired pneumonia (i.e. classifies patients into risk classes 1-5), a common and costly clinical problem. Most of the variables for the automated application were obtained by writing queries based on output generated by MedLEE1, a natural language processor that encodes clinical information in text. Comorbidities, vital signs, and symptoms from discharge summaries as well as information from chest x-ray reports were used. The results were very good because when compared with a reference standard obtained manually by an independent expert, the automated application demonstrated an accuracy, sensitivity, and specificity of 93%, 92%, and 93% respectively for processing discharge summaries, and 96%, 87%, and 98% respectively for chest x-rays. The accuracy for vital sign values was 85%, and the accuracy for determining the exact risk class was 80%. The remaining 20% that did not match exactly differed by only one class
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| 650 |
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|a Journal Article
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| 650 |
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4 |
|a Research Support, U.S. Gov't, P.H.S.
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| 700 |
1 |
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|a Knirsch, C
|e verfasserin
|4 aut
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| 700 |
1 |
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|a Shagina, L
|e verfasserin
|4 aut
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| 700 |
1 |
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|a Hripcsak, G
|e verfasserin
|4 aut
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| 773 |
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|i Enthalten in
|t Proceedings. AMIA Symposium
|d 1998
|g (1999) vom: 23., Seite 256-60
|w (DE-627)NLM098642928
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|g year:1999
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|a AR
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| 952 |
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|j 1999
|b 23
|h 256-60
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