Enhancing COVID-19 vaccine effectiveness evidence generation using tokenized immunization registries.

Area of Science:

• Public Health
• Health Informatics
• Immunization Research

Background:

• Accurate tracking of COVID-19 vaccine uptake is crucial for public health surveillance and policy.
• Administrative claims data alone may underestimate vaccine coverage.
• State vaccine registries offer a more comprehensive vaccination record.

Purpose of the Study:

• To introduce a novel data ecosystem linking claims and registry data.
• To quantify the improvement in documented COVID-19 vaccine uptake using this integrated approach.
• To compare vaccine capture rates across different COVID-19 vaccine formulations.

Main Methods:

• De-identified administrative claims data were tokenized and linked to state vaccine registry data.
• Vaccine uptake was measured using claims data alone versus claims data supplemented with registry data.
• Analysis included original wildtype, BA.4/5-adapted bivalent, and XBB.1.5-adapted COVID-19 vaccine formulations.

Main Results:

• Integration increased documented primary wildtype series uptake from 20% to 57%.
• Capture of BA.4/5-adapted bivalent and XBB.1.5-adapted vaccines increased from 7% to 10% and 6% to 8%, respectively.
• Claims data primarily captured vaccinations via drug codes, and Medicaid-insured individuals were less represented.

Conclusions:

• The addition of state vaccine registries significantly boosted COVID-19 vaccine capture rates (up to 182% for wildtype).
• Tokenization of claims data to vaccine registries enables more precise vaccine uptake and effectiveness estimations.
• This novel data ecosystem enhances public health surveillance capabilities for vaccination campaigns.