The impact of electronic medical records data sources on an adverse drug event quality measure
The impact of electronic medical records data sources on an adverse drug event quality measure
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DOI：
10.1136/jamia.2009.002451
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发表时间：
2010-03-01
影响因子：
6.4
通讯作者：
Banade, Dalksha
中科院分区：
文献类型：
--
作者：
Kahn, Michael G.;Banade, Dalksha
目的研究从电子病历系统中提取的计费和临床数据对联合委员会ORYX项目中批准使用的药物不良事件（ADE）质量指标计算的影响，设计美国儿童健康公司的“使用救援剂-ADE触发器”质量度量使用儿科健康信息系统（PHIS）数据仓库中包含的药物账单数据来创建联合委员会-一个经过验证的质量度量。使用类似的查询，我们使用PHIS加上从我们的电子病历（EMR）系统中提取的四个数据源计算质量指标：收取的药物、发出的药物订单、收取相关费用的药物订单（收取费用的订单）和管理的药物。使用5个数据集计算分母和分子。报告的质量措施是ADE率（分子/计数器。结果计数器，分子和率的显着差异，计算从不同的数据来源在一个单一的机构的EMR。差异是由于各机构之间可能相似的常见临床实践和任何其他机构不太可能存在的独特工作流程实践。差异的大小将显着改变我们的机构相比，其他PHIS institutions.Conclusions国家比较排名更详细的临床信息可能会导致质量措施，是不可比的机构，由于机构的具体工作流程，使用EMR衍生的数据暴露的差异。
Objective To examine the impact of billing and clinical data extracted from an electronic medical record system on the calculation of an adverse drug event (ADE) quality measure approved for use in The Joint Commission's ORYX program, a mandatory national hospital quality reporting system.Design The Child Health Corporation of America's "Use of Rescue Agents-ADE Trigger" quality measure uses medication billing data contained in the Pediatric Health Information Systems (PHIS) data warehouse to create The Joint Commission-a p proved quality measure. Using a similar query, we calculated the quality measure using PHIS plus four data sources extracted from our electronic medical record (EMR) systems medications charged, medication orders placed, medication orders with associated charges (orders charged), and medications administered.Measurements Inclusion and exclusion criteria were identical for all queries. Denominators and numerators were calculated using the five data sets. The reported quality measure is the ADE rate (numerater/denominators.Results Significant differences in denominators, numerators, and rates were calculated from different data sources within a single institution's EMR. Differences were due to both common clinical practices that may be similar across institutions and unique workflow practices not likely to be present at any other institution. The magnitude of the differences would significantly alter the national comparative ranking of our institution compared to other PHIS institutions.Conclusions More detailed clinical information may result in quality measures that are not comparable across institutions due institution-specific workflow, differences that are exposed using EMR-derived data.