Validating emergency department vital signs using a data quality engine for data warehouse.

The open medical informatics journal Pub Date : 2013-12-13 eCollection Date: 2013-01-01 DOI:10.2174/1874431101307010034
N Genes, D Chandra, S Ellis, K Baumlin
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引用次数: 15

Abstract

Background: Vital signs in our emergency department information system were entered into free-text fields for heart rate, respiratory rate, blood pressure, temperature and oxygen saturation.

Objective: We sought to convert these text entries into a more useful form, for research and QA purposes, upon entry into a data warehouse.

Methods: We derived a series of rules and assigned quality scores to the transformed values, conforming to physiologic parameters for vital signs across the age range and spectrum of illness seen in the emergency department.

Results: Validating these entries revealed that 98% of free-text data had perfect quality scores, conforming to established vital sign parameters. Average vital signs varied as expected by age. Degradations in quality scores were most commonly attributed logging temperature in Fahrenheit instead of Celsius; vital signs with this error could still be transformed for use. Errors occurred more frequently during periods of high triage, though error rates did not correlate with triage volume.

Conclusions: In developing a method for importing free-text vital sign data from our emergency department information system, we now have a data warehouse with a broad array of quality-checked vital signs, permitting analysis and correlation with demographics and outcomes.

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使用数据仓库的数据质量引擎验证急诊科生命体征。
背景:我们急诊科信息系统中的生命体征以自由文本形式输入心率、呼吸频率、血压、体温和血氧饱和度。目的:我们试图将这些文本条目转换成更有用的形式,用于研究和QA目的,在进入数据仓库时。方法:我们推导了一系列规则,并对转换后的值进行质量评分,这些值符合急诊科所见的年龄范围和疾病谱的生命体征的生理参数。结果:验证这些条目显示98%的自由文本数据具有完美的质量分数,符合既定的生命体征参数。平均生命体征随着年龄的变化而变化。质量分数的下降最常见的原因是测井温度是华氏温度,而不是摄氏度;有这个错误的生命体征仍然可以被转换使用。虽然错误率与分诊量无关,但在分诊率高的时期,错误率发生得更频繁。结论:在开发一种从急诊科信息系统导入自由文本生命体征数据的方法时,我们现在拥有一个数据仓库,其中包含大量经过质量检查的生命体征,可以进行人口统计学和结果的分析和关联。
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