Brown Carolyn A, Londhe Ajit A, He Fang, Cheng Alvan, Ma Junjie, Zhang Jie, Brooks Corinne G, Sprafka J Michael, Roehl Kimberly A, Carlson Katherine B, Page John H
Center for Observational Research, Amgen, Inc., Thousand Oaks, CA, USA.
Woodford Research Associates, Thousand Oaks, CA, USA.
Clin Epidemiol. 2022 May 23;14:699-709. doi: 10.2147/CLEP.S355086. eCollection 2022.
In order to identify and evaluate candidate algorithms to detect COVID-19 cases in an electronic health record (EHR) database, this study examined and compared the utilization of acute respiratory disease codes from February to August 2020 versus the corresponding time period in the 3 years preceding.
De-identified EHR data were used to identify codes of interest for candidate algorithms to identify COVID-19 patients. The number and proportion of patients who received a SARS-CoV-2 reverse transcriptase polymerase chain reaction (RT-PCR) within ±10 days of the occurrence of the diagnosis code and patients who tested positive among those with a test result were calculated, resulting in 11 candidate algorithms. Sensitivity, specificity, and likelihood ratios assessed the candidate algorithms by clinical setting and time period. We adjusted for potential verification bias by weighting by the reciprocal of the estimated probability of verification.
From January to March 2020, the most commonly used diagnosis codes related to COVID-19 diagnosis were R06 (dyspnea) and R05 (cough). On or after April 1, 2020, the code with highest sensitivity for COVID-19, U07.1, had near perfect adjusted sensitivity (1.00 [95% CI 1.00, 1.00]) but low adjusted specificity (0.32 [95% CI 0.31, 0.33]) in hospitalized patients.
Algorithms based on the U07.1 code had high sensitivity among hospitalized patients, but low specificity, especially after April 2020. None of the combinations of ICD-10-CM codes assessed performed with a satisfactory combination of high sensitivity and high specificity when using the SARS-CoV-2 RT-PCR as the reference standard.
为了识别和评估用于在电子健康记录（EHR）数据库中检测新冠肺炎病例的候选算法，本研究检查并比较了2020年2月至8月与前三年相应时间段内急性呼吸道疾病代码的使用情况。
使用去识别化的EHR数据来确定候选算法识别新冠肺炎患者的感兴趣代码。计算在诊断代码出现前后±10天内接受严重急性呼吸综合征冠状病毒2逆转录酶聚合酶链反应（RT-PCR）检测的患者数量和比例，以及检测结果呈阳性的患者在接受检测患者中的比例，从而得出11种候选算法。敏感性、特异性和似然比按临床环境和时间段评估候选算法。我们通过以估计验证概率的倒数加权来调整潜在的验证偏倚。
2020年1月至3月，与新冠肺炎诊断相关的最常用诊断代码是R06（呼吸困难）和R05（咳嗽）。在2020年4月1日或之后，对新冠肺炎敏感性最高的代码U07.1在住院患者中的调整后敏感性接近完美（1.00 [95% CI 1.00, 1.00]），但调整后特异性较低（0.32 [95% CI 0.31, 0.33]）。
基于U07.1代码的算法在住院患者中具有高敏感性，但特异性较低，尤其是在2020年4月之后。当以严重急性呼吸综合征冠状病毒2 RT-PCR作为参考标准时，所评估的国际疾病分类第十次修订本临床修订版（ICD-10-CM）代码组合中，没有一个在高敏感性和高特异性的令人满意组合方面表现良好。
