Development of an electronic medical record-based algorithm to identify patients with unknown HIV status
Development of an electronic medical record-based algorithm to identify patients with unknown HIV status
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DOI：
10.1080/09540121.2014.911813
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发表时间：
2014-01-01
影响因子：
1.7
通讯作者：
Zingman, Barry S.
中科院分区：
文献类型：
--
作者：
Felsen, Uriel R.;Bellin, Eran Y.;Zingman, Barry S.
艾滋病毒感染状况不明的个体有感染未确诊艾滋病毒的风险，但尚未描述识别这些个体的实用可靠方法。我们开发了一种算法，使用大型医疗保健系统的电子病历（EMR）中的数据来识别HIV状态未知的患者。我们开发了基于EMR的标准，将患者分类为已知状态（HIV阳性或HIV阴性）或未知状态，并将这些标准应用于2008年至2012年附属医疗保健系统中的所有患者。通过将算法结果的随机样本与参考标准医疗记录审查进行比较，计算了识别未知HIV状态患者的算法的性能特征。该算法将所有患者分类为已知或未知的HIV状态。其识别未知状态患者的敏感性和特异性为99.4%（95% CI：96.5-100%）和95.2%（95% CI：83.8-99.4%），阳性和阴性预测值分别为98.7%（95% CI：95.5-99.8%）和97.6%（95% CI：87.1-99.1%）。使用常见的EMR数据，我们的算法具有较高的灵敏度和特异性，用于识别HIV状态未知的患者。该算法可以告知旨在测试未经测试的扩展的HIV测试策略。
Individuals with unknown HIV status are at risk for undiagnosed HIV, but practical and reliable methods for identifying these individuals have not been described. We developed an algorithm to identify patients with unknown HIV status using data from the electronic medical record (EMR) of a large health care system. We developed EMR-based criteria to classify patients as having known status (HIV-positive or HIV-negative) or unknown status and applied these criteria to all patients seen in the affiliated health care system from 2008 to 2012. Performance characteristics of the algorithm for identifying patients with unknown HIV status were calculated by comparing a random sample of the algorithm's results to a reference standard medical record review. The algorithm classifies all patients as having either known or unknown HIV status. Its sensitivity and specificity for identifying patients with unknown status are 99.4% (95% CI: 96.5-100%) and 95.2% (95% CI: 83.8-99.4%), respectively, with positive and negative predictive values of 98.7% (95% CI: 95.5-99.8%) and 97.6% (95% CI: 87.1-99.1%), respectively. Using commonly available data from an EMR, our algorithm has high sensitivity and specificity for identifying patients with unknown HIV status. This algorithm may inform expanded HIV testing strategies aiming to test the untested.