Analysis of anesthesia screens for rule-based data quality assessment opportunities

被引：0

作者：

Wang Z. ^{[1
]}

Penning M. ^{[2
]}

Zozus M. ^{[2
]}

机构：

[1] University of Arkansas at Little Rock, United States

[2] University of Arkansas for Medical Sciences, United States

来源：

Studies in Health Technology and Informatics | 2019年 / 257卷

关键词：

data quality; Electronic health record;

D O I：

10.3233/978-1-61499-951-5-473

中图分类号：

学科分类号：

摘要：

A rules-based data quality assessment system in electronic health record was explored through compilation of over six thousand data quality rules and twenty-two rule templates. To overcome the lack of knowledge sources and identify additional rules or rule templates, thirty-three anesthesia (perioperative period) EHR screens were reviewed. We analyzed the data elements appearing on anesthesia screens and relationships between them to identify new data quality rules and rule templates relevant to anesthesia care. We present the review process as well as new rules and rule templates identified. We found decomposition and analysis of EHR screens a viable mechanism for acquisition of new data quality rules and proved the number of rules likely tractable and their management scalable. © 2019 American Psychological Association Inc. All rights reserved.

引用

页码：473 / 478

页数：5

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