Institute for Health Research, Kaiser Permanente Colorado, Aurora, CO, USA.
Department of Pediatrics, University of Colorado School of Medicine, Aurora, CO, USA.
Public Health Rep. 2023 May-Jun;138(3):456-466. doi: 10.1177/00333549221099932. Epub 2022 Jun 8.
Having accurate influenza vaccination coverage estimates can guide public health activities. The objectives of this study were to (1) validate the accuracy of electronic health record (EHR)-based influenza vaccination data among pregnant women compared with survey self-report and (2) assess whether survey respondents differed from survey nonrespondents by demographic characteristics and EHR-based vaccination status.
This study was conducted in the Vaccine Safety Datalink, a network of 8 large medical care organizations in the United States. Using EHR data, we identified all women pregnant during the 2018-2019 or 2019-2020 influenza seasons. Surveys were conducted among samples of women who did and did not appear vaccinated for influenza according to EHR data. Separate surveys were conducted after each influenza season, and respondents reported their influenza vaccination status. Analyses accounted for the stratified design, sampling probability, and response probability.
The survey response rate was 50.5% (630 of 1247) for 2018-2019 and 41.2% (721 of 1748) for 2019-2020. In multivariable analyses combining both survey years, non-Hispanic Black pregnant women had 3.80 (95% CI, 2.13-6.74) times the adjusted odds of survey nonresponse; odds of nonresponse were also higher for Hispanic pregnant women and women who had not received (per EHR data) influenza vaccine during current or prior influenza seasons. The sensitivity, specificity, and positive predictive value of EHR documentation of influenza vaccination compared with self-report were ≥92% for both survey years combined. The negative predictive value of EHR-based influenza vaccine status was 80.5% (95% CI, 76.7%-84.0%).
EHR-based influenza vaccination data among pregnant women were generally concordant with self-report. New data sources and novel approaches to mitigating nonresponse bias may be needed to enhance influenza vaccination surveillance efforts.
获得准确的流感疫苗接种覆盖率估计值有助于指导公共卫生活动。本研究的目的是：(1) 验证电子健康记录 (EHR) 中基于孕妇的流感疫苗接种数据与调查自我报告相比的准确性；(2) 评估调查应答者是否在人口统计学特征和基于 EHR 的疫苗接种状态方面与调查未应答者存在差异。
本研究在美国 8 个大型医疗保健组织网络中的疫苗安全数据链接中进行。使用 EHR 数据，我们确定了所有在 2018-2019 年或 2019-2020 年流感季节期间怀孕的女性。根据 EHR 数据，对未接种和已接种流感疫苗的女性进行了抽样调查。在每个流感季节之后分别进行了单独的调查，受访者报告了他们的流感疫苗接种情况。分析考虑了分层设计、抽样概率和应答概率。
2018-2019 年调查的应答率为 50.5%（630/1247），2019-2020 年为 41.2%（721/1748）。在结合了两个调查年份的多变量分析中，非西班牙裔黑人孕妇的调查未应答的调整比值比为 3.80（95%CI，2.13-6.74）；西班牙裔孕妇和既往或当前流感季节未接种（根据 EHR 数据）流感疫苗的孕妇，其未应答的可能性也更高。2018-2019 年两个调查年份的 EHR 记录流感疫苗接种情况与自我报告相比，灵敏度、特异性和阳性预测值均≥92%。基于 EHR 的流感疫苗接种状态的阴性预测值为 80.5%（95%CI，76.7%-84.0%）。
孕妇的 EHR 记录流感疫苗接种数据与自我报告基本一致。可能需要新的数据来源和减轻无应答偏倚的新方法来加强流感疫苗接种监测工作。
