Patel Arshiya, Payne Amanda B, Currie Dustin W, Franceschini Thomas, Gensheimer Amber, Lutgring Joseph D, Reddy Sujan C, Hatfield Kelly M
Division of Healthcare Quality Promotion, National Center for Emerging and Zoonotic Infectious Diseases, Centers for Disease Control and Prevention, Atlanta, GA, USA; Professional Services Business Unit, Chenega Enterprise, Systems, and Solutions, Anchorage, AK, USA.
Coronavirus and Other Respiratory Viruses Division, National Center for Immunizations and Respiratory Diseases, Centers for Disease Control and Prevention, Atlanta, GA, USA.
J Am Med Dir Assoc. 2025 Mar;26(3):105440. doi: 10.1016/j.jamda.2024.105440. Epub 2025 Jan 18.
This study aimed to evaluate the utility of electronic health record (EHR) diagnosis codes for monitoring SARS-CoV-2 infections among nursing home residents.
A retrospective cohort study design was used to analyze data collected from nursing homes operating under the tradename Signature Healthcare between January 2022 and June 2023.
Data from 31,136 nursing home residents across 76 facilities in Kentucky, Tennessee, Indiana, Ohio, North Carolina, Georgia, Alabama, and Virginia were included.
Resident demographics, diagnosis codes associated with clinical diagnoses (including COVID-19), and SARS-CoV-2 testing information were collected from the EHR and supplemental testing data sources. We described the rates of infection and the clinical characteristics of residents with incident-positive SARS-CoV-2 tests and new-onset COVID-19 diagnoses. Positive predictive values (PPVs) of COVID-19 diagnosis codes were calculated for residents stratified by whether a resident was continuously present in a facility for ±3 days from the diagnosis onset date listed in EHRs, using positive SARS-CoV-2 tests to confirm infection.
A total of 4876 incident-positive SARS-CoV-2 tests and 6346 new-onset COVID-19 diagnoses were recorded during the study period. Weekly rates of new-onset diagnoses were significantly higher than positive test rates, although trends followed similar trajectories. Among residents continuously present in the nursing home ±3 days from the diagnosis onset date, the PPV of COVID-19 diagnosis codes was high (3395 of 3685 = 92%; 95% CI, 91%-93%). The PPV among this group significantly varied by study quarter (P < .001). The PPV was substantially lower for 2661 diagnoses among residents not continuously present in the nursing home (24%; 95% CI, 22%-26%).
This study demonstrates the utility of diagnosis codes for assessment of COVID-19 epidemiology and trends when testing data are unavailable for residents during their stay in a nursing home. Future research should explore strategies to evaluate the utility of diagnosis codes at admission and discharge to nursing homes to enhance surveillance efforts.
本研究旨在评估电子健康记录(EHR)诊断代码在监测疗养院居民中SARS-CoV-2感染情况的效用。
采用回顾性队列研究设计,分析2022年1月至2023年6月期间以Signature Healthcare为商号运营的疗养院收集的数据。
纳入了肯塔基州、田纳西州、印第安纳州、俄亥俄州、北卡罗来纳州、佐治亚州、阿拉巴马州和弗吉尼亚州76家疗养院中31136名居民的数据。
从电子健康记录和补充检测数据源收集居民人口统计学信息、与临床诊断相关的诊断代码(包括COVID-19)以及SARS-CoV-2检测信息。我们描述了SARS-CoV-2检测呈阳性的居民和新发COVID-19诊断居民的感染率及临床特征。根据居民在电子健康记录中列出的诊断起始日期前后±3天是否持续居住在疗养院,对居民进行分层,计算COVID-19诊断代码的阳性预测值(PPV),以SARS-CoV-2检测阳性确认感染情况。
在研究期间共记录了4876例SARS-CoV-2检测呈阳性事件和6346例新发COVID-19诊断。新发诊断的周率显著高于阳性检测率,尽管趋势相似。在诊断起始日期前后±3天持续居住在疗养院的居民中,COVID-19诊断代码的PPV较高(3685例中的3395例 = 92%;95%置信区间,91%-93%)。该组中的PPV在研究季度间有显著差异(P < .001)。对于未持续居住在疗养院的居民中的2661例诊断,PPV显著较低(24%;95%置信区间,22%-26%)。
本研究证明了在疗养院居民住院期间无法获取检测数据时,诊断代码在评估COVID-19流行病学和趋势方面的效用。未来研究应探索评估疗养院入院和出院时诊断代码效用的策略,以加强监测工作。