Ascertainment of vaccination status by self-report versus source documentation: Impact on measuring COVID-19 vaccine effectiveness.

BACKGROUND: During the COVID-19 pandemic, self-reported COVID-19 vaccination might facilitate rapid evaluations of vaccine effectiveness (VE) when source documentation (e.g., immunization information systems [IIS]) is not readily available. We evaluated the concordance of COVID-19 vaccination status ascertained by self-report versus source documentation and its impact on VE estimates. METHODS: Hospitalized adults (≥18 years) admitted to 18 U.S. medical centers March-June 2021 were enrolled, including COVID-19 cases and SARS-CoV-2 negative controls. Patients were interviewed about COVID-19 vaccination. Abstractors simultaneously searched IIS, medical records, and other sources for vaccination information. To compare vaccination status by self-report and documentation, we estimated percent agreement and unweighted kappa with 95% confidence intervals (CIs). We then calculated VE in preventing COVID-19 hospitalization of full vaccination (2 doses of mRNA product ≥14 days prior to illness onset) independently using data from self-report or source documentation. RESULTS: Of 2520 patients, 594 (24%) did not have self-reported vaccination information to assign vaccination group; these patients tended to be more severely ill. Among 1924 patients with both self-report and source documentation information, 95.0% (95% CI: 93.9-95.9%) agreement was observed, with a kappa of 0.9127 (95% CI: 0.9109-0.9145). VE was 86% (95% CI: 81-90%) by self-report data only and 85% (95% CI: 81-89%) by source documentation data only. CONCLUSIONS: Approximately one-quarter of hospitalized patients could not provide self-report COVID-19 vaccination status. Among patients with self-report information, there was high concordance with source documented status. Self-report may be a reasonable source of COVID-19 vaccination information for timely VE assessment for public health action.

Duke Scholars

Author Christopher Lindsell Biostatistics & Bioinformatics, Division of Biostatistics