How Data Gaps Impact COVID-19 Vaccine Hesitancy
This opinion piece was authored by Dr. Michelle Fiscus, a subject matter expert that consults for AIM. Note: this opinion piece is not an official AIM statement.
As highlighted in the recent commentary, Supporting immunization programs to address COVID-19 vaccine hesitancy: Recommendations for national and community-based stakeholders, the COVID-19 pandemic has underscored the inability of the current data infrastructure to clearly describe the gaps in COVID-19 vaccination rates (Wells, 2022).
For years, immunization programs called for interoperability and data sharing, not only between immunization information systems (IIS), electronic health records (EHRs), health information technology programs, and government agencies, but also between state and federal governments. Prior to the pandemic, relatively little progress was made as programs managed competing priorities and the lack of flexibility in federal funding. As a result of the pandemic, immunization programs have much-needed (though short-term) funding to build out these systems. However, developing the capacity to accomplish the work often still proves challenging.
The pandemic presented an unprecedented need for collaboration and policy coordination between public health and Medicaid officials (Association of Immunization Managers, 2021). When it came time to vaccinate against COVID-19, the inability of public health data systems to provide a clear picture of which populations were partially vaccinated, which were fully vaccinated, and who had refused vaccines (and why) hampered efforts to provide outreach to populations in need. State Medicaid program directors are aware that significant disparities exist between vaccination rates among Medicaid and privately insured beneficiaries (NASHP, 2021). However, since many COVID-19 vaccinators did not submit charges to Medicaid, the programs are unable to identify which of Medicaid members still need to be vaccinated and, therefore, often do not know how best to target outreach.
While jurisdictional IIS may collect insurance information, most IIS programs do not share this data with Medicaid programs. Similarly, pregnancy status is not captured in an IIS due to the lack of an international reporting standard, thus making it impossible to determine if pregnant people are getting vaccinated and to design targeted outreach efforts. As low-income, minority, and pregnant people are at higher risk for severe disease and poor outcomes from COVID-19, the inability to accurately identify individuals who would benefit from outreach means opportunities to reduce disparities are missed.
As suggested by Wells, et. al., federal and state governments must make the funding of public health data systems a priority by investing in the development and standardization of IIS demographic variables and facilitating the timely hiring of skilled IIS staff and epidemiologists to build the infrastructure and analyze these data. Healthcare organizations can play a critical role in the assurance of data quality by requiring and incentivizing healthcare providers to capture demographic information in EHRs and IIS. These systems should not only be able to demonstrate which populations are and are not getting vaccinated, but why they are not getting vaccinated.
With the capture of robust data and the ability to analyze and share that data across systems, immunization and Medicaid programs can efficiently and deliberately direct resources to reach individuals who lack access to vaccination or who might benefit from tailored education and messaging that builds vaccine confidence. Funding to these programs must be reliable and sustainable if public health is to bring its information systems into the 21st century and use readily available technology to reduce disparities and optimize public health outcomes.
Read the complete article, Supporting immunization programs to address COVID-19 vaccine hesitancy: Recommendations for national and community-based stakeholders, here.