Automated evaluation of electronic discharge notes to assess quality of care for cardiovascular diseases using Medical Language Extraction and Encoding System (MedLEE)

被引：20
作者：
Chiang, Jung-Hsien [1 ,2 ]
Lin, Jou-Wei [3 ,4 ]
Yang, Chen-Wei [1 ,2 ]
机构：
[1] Natl Cheng Kung Univ, Dept Comp Sci, Tainan 70101, Taiwan
[2] Natl Cheng Kung Univ, Inst Med Informat, Tainan 70101, Taiwan
[3] Natl Taiwan Univ Hosp, Ctr Cardiovasc, Yun Lin Branch, Dou Liou City, Yun Lin, Taiwan
[4] Natl Taiwan Univ, Dept Med, Coll Med, Tainan, Taiwan
来源：
JOURNAL OF THE AMERICAN MEDICAL INFORMATICS ASSOCIATION | 2010年 / 17卷 / 03期
关键词：
ST-SEGMENT ELEVATION; MYOCARDIAL-INFARCTION; INFORMATION; RECORDS;
D O I：
10.1136/jamia.2009.000182
中图分类号：
TP [自动化技术、计算机技术];
学科分类号：
0812 ;
摘要：
The objective of this study was to develop and validate an automated acquisition system to assess quality of care (QC) measures for cardiovascular diseases. This system combining searching and retrieval algorithms was designed to extract QC measures from electronic discharge notes and to estimate the attainment rates to the current standards of care. It was developed on the patients with ST-segment elevation myocardial infarction and tested on the patients with unstable angina/non-ST-segment elevation myocardial infarction, both diseases sharing almost the same QC measures. The system was able to reach a reasonable agreement (kappa value) with medical experts from 0.65 (early reperfusion rate) to 0.97 (beta-blockers and lipid-lowering agents before discharge) for different QC measures in the test set, and then applied to evaluate QC in the patients who underwent coronary artery bypass grafting surgery. The result has validated a new tool to reliably extract QC measures for cardiovascular diseases.
引用
收藏
页码：245 / 252
页数：8
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