The Journal of School Nursing2025, Vol. 41(3) 325–332© The Author(s) 2022Article reuse guidelines:sagepub.com/journals-permissionsDOI: 10.1177/10598405221130701journals.sagepub.com/home/jsn
AbstractRecent trends in vaccine hesitancy have brought to light the importance of using accurate school vaccination data. This study evaluated the accuracy of a pilot statewide kindergarten vaccination survey in Oklahoma. School vaccination and exemption data were collected from November 2017 to April 2018 via the Research Electronic Data Capture system. A multivariable linear regression model was used to evaluate the relationship between students who are up to date for all vaccines comparing school reported and Oklahoma State Department of Health-validated data. Adjusted vaccination data were overestimated by 1.0% among public schools and 3.3% among private schools. These results were validated by a random audit of participating schools finding the school-reported vaccination data to be overestimated by 0.6% compared to true student immunization records on file. Our analysis indicates that school-reported vaccination data are sufficiently valid. Immunization record audits provide confidence in available data, which drives evidence-based decision-making.
Keywordsschool health, vaccination, kindergarten, community health, data validation, school immunization audit
The COVID-19 pandemic has shown a spotlight on the role vaccination plays in society and consequently, parents and lawmakers are re-evaluating vaccine requirements for school entry. However, maintaining high vaccination coverage is critically important to maintain herd immunity against vaccine-preventable diseases (Bramer et al., 2020; Patel Murthy et al., 2021; Santoli et al., 2020, 2021; World Health Organization, 2012). School vaccination assessments conducted at the local level are useful to detect geographic pockets of low vaccination coverage (Mellerson et al., 2020; Omer et al., 2009; Patel et al., 2019; Seither et al., 2021). Communities with low vaccination coverage are vulnerable to vaccine-preventable disease outbreaks, even when national-level coverage is high (Omer et al., 2009; Patel et al., 2019). Recent trends in vaccine hesitancy have brought to light the importance of using accurate school vaccination data to track vaccine uptake and the continued use of non-medical exemptions (Bednarczyk et al., 2019; Olive et al., 2018). School vaccination data may also provide visibility into trends of school choice as a result of strengthening immunization laws (Patel et al., 2022). In addition to emergency preparedness, local-level school vaccination data can be used to advance applied research, media transparency, and community health education programs (Mellerson et al., 2020).
Each year, the Advisory Committee on Immunization Practices (ACIP) recommends vaccination schedules for children and adults (Wodi et al., 2022). The recommendations by the ACIP are used to guide the implementation of vaccination requirements for school entry, though requirements may vary across states (Mellerson et al., 2020; Orenstein & Hinman, 1999; Seither et al., 2021). Most state vaccination requirements provide the option of completing a certificate of exemption for all or specific vaccines (Omer et al., 2009; Orenstein & Hinman, 1999; Smith et al., 2017). Exemptions to vaccinations for school entry may be granted due to medical, religious, and/or personal purposes, with occurrence varying from state to state (Bednarczyk et al., 2019; Hinman et al., 2002; Smith et al., 2017).
In Oklahoma, school vaccination requirements are codified by the Oklahoma Immunization Act passed in 1970 (“O.K. §70–1210.191,”). The Act gives the Oklahoma State Department of Health (OSDH) the authority to determine the vaccines and number of doses required for school entry into childcare programs and school (“O.K. §70–1210.191,”). Each year, Oklahoma participates in the Centers for Disease Control and Prevention (CDC) School Vaccination Assessment. The CDC School Vaccination Assessment quantifies the distribution of vaccination coverage and exemptions across the United States (Seither et al., 2021). Each public health jurisdiction’s immunization program has the flexibility to independently determine the method of data collection for annual submission to CDC (Mellerson et al., 2020; Seither et al., 2021).
To date, OSDH has relied on schools voluntarily self-reporting data on vaccination and exemptions. The CDC recommends states relying on self-reported data conduct validation studies to assess the accuracy of said data (Mellerson et al., 2020). Validation studies of state and local-level school vaccination assessments are uncommon in the literature. The most recent publication for such a validation occurred in 2007 where the Colorado Department of Public Health and Environment found that schools over-estimated vaccination coverage by 13.1% (Stanwyck et al., 2007).
Given this gap in available evidence, development of new data technologies, and renewed interest in school vaccination rates due to recent trends in vaccine hesitancy, we evaluated the accuracy of the Oklahoma Kindergarten Vaccination Assessment conducted in 2018. Our evaluation process comprised two strategies: 1) compare the accuracy of school self-reported data versus OSDH-validated data, and 2) perform audits of in-school student immunization records to compare the accuracy of vaccination data between public and private schools in Oklahoma.
The Oklahoma Kindergarten Vaccination Assessment is designed to quantify the annual distribution of vaccination coverage and exemptions for all kindergarten students in Oklahoma. Data were collected on students enrolled in a participating public or private school in the 2017–2018 school year. The assessment collected data on vaccination status for the six vaccines in the 4:3:2:3:2:1 series (i.e., diphtheria/tetanus/pertussis, polio, measles/mumps/rubella, hepatitis B, hepatitis A, and varicella). Vaccine-specific exemption data were also collected and stratified by personal, medical, or religious purposes. We partnered with the Oklahoma State Department of Education (ODE) and Oklahoma Private School Accrediting Association (OPSAC) to solicit participation from all 846 public schools and all 99 private schools in the state.
Schools were asked to submit data to OSDH via the Research Electronic Data Capture (REDCap) system (a secure, web-based application for survey administration and data entry) (Harris et al., 2009). Schools were asked to submit: 1) aggregate data on student vaccination and exemptions, by vaccine and exemption types and 2) a file containing a line list of vaccine and exemption data by student to verify such reported totals. If a participating school provided inadequate documentation of the aforementioned items, it was excluded from the analysis. Schools could submit data files via two techniques: 1) an OSDH standardized template or 2) school records in a customized report. Both the standardized template and customized reports collected for each student included a unique identifier, date of birth, history or laboratory evidence of previous disease, up-to-date status, and exemptions by type. The only difference between the two reporting formats is that the OSDH standardized template collected the number of doses by vaccine type but not the date of vaccine dose administration, whereas the customized reports collected the date of vaccine dose administration. OSDH staff provided technical assistance through email and phone communications. Step-by-step instructions were created and distributed to schools to assist in determining vaccination and exemption status to generate aggregate data for their school kindergarten population. Data were collected on a rolling basis from November 2017 to April 2018.
We validated the aggregate data submitted by schools by reviewing each file in REDCap. Following review, a new set of OSDH-validated aggregate data on vaccination and exemptions were generated. The new OSDH-validated dataset was compared to the original aggregate dataset submitted by schools. A simple random sample of schools using the OSDH standardized template to submit data were selected assuming an effect size of 15% and power of 80% using the proc surveyselect procedure in SAS v. 9.4. We audited these submissions by requesting redacted copies of their in-school student immunization records on file.
Vaccination status was determined by counting valid vaccine doses received at or after the ACIP recommended age and time interval for the 4:3:2:3:2:1 series. Compliance with full vaccination coverage in Oklahoma is defined as ≥four DTaP/DTP/DT doses, ≥three polio doses, ≥two MMR doses, ≥three hepatitis B doses, ≥two hepatitis A doses, and ≥one varicella dose (4:3:2:3:2:1 series). Exemptions are categorized as medical, religious, or personal. The denominator for each calculated vaccination and exemption rate was based on the current enrollment during the 2017–2018 school year obtained from the ODE and a query of all OSPAC schools. The primary outcome of interest was the absolute mean difference in the proportion of kindergarten students who are up to date for all vaccines between the school reported responses and the OSDH validated responses. The difference was calculated by subtracting the school reported proportion from the OSDH validated proportion. All validation analyses were stratified by school type (public vs. private). Religious and personal exemptions were combined to form a non-medical exemption category and compared to medical exemptions.
We used multivariable linear regression to evaluate factors potentially impacting discrepancies in vaccination rates between the school report and the OSDH-validated data source. These factors included school personnel type (administrator, healthcare staff, and other employee), data submission technique (OSDH standardized template and school records in a customized report), and county designation (urban and rural). All variables were evaluated for inclusion in the final model with consideration for possible confounding, collinearity, and interaction. A school characteristic was deemed a confounder if its omission from the model impacted the coefficient estimates by ten percent or more. School district was evaluated as a random effect to test for cluster variability among schools. We evaluated private schools for non-response bias by examining the association of school size and county location between private schools that did and did not respond. This was not done for public schools given the high level of participation. School size was categorized as small (0–32 students), medium (33–75 students), or large (70 or more students). We used studentized deleted residuals to evaluate the assumptions of the linear regression model. An alpha value of 0.05 was used for all statistical tests. The data analysis for this study was conducted using SAS v. 9.4. All data were collected for public health surveillance purposes in accordance with relevant state statutes and policies (O.K. §70) and granted exempted review by the University of Oklahoma Health Sciences Center Institutional Review Board.
Seven hundred and fifty-three (89.0%) public schools and 51 (51.5%) private schools with enrolled kindergartners voluntarily responded to the Oklahoma Kindergarten Vaccination Assessment in 2018. This accounted for 46,692 (90.6%) of all kindergarten students enrolled in public schools and 1,226 (58.9%) of all enrolled kindergarten students enrolled in private schools in the state. Overall, 42,597 (91.2%) of kindergarten students enrolled in participating public schools with records on file were considered up to date according to the 4:3:2:3:2:1 series compared to 1,035 (84.4%) of kindergarten students enrolled in participating private schools (see Supplemental Document). Nine hundred and seventy-five (2.1%) kindergarten students in participating public schools had an exemption certificate on file for one or more vaccines compared to 69 (5.6%) kindergarten students in participating private schools.
Two hundred and sixty-two (34.8%) public schools did not provide aggregate data on student vaccination and exemptions and were excluded from the analysis. Among the remaining 491 public schools, 382 (50.7%) used the OSDH standard template and 109 (14.4%) used school records in a customized report (Table 1). Among private schools, 46 (90.2%) used the OSDH standard template and 5 (9.8%) used school records in a customized report. We were unable to validate responses for 42 schools (41 public and 1 private) due to inadequate documentation with either no student-level data or excessive missing values in the report. We determined reports with missing data of 20% or more would be too resource intensive to correct. In total, we excluded 304 (37.8%) schools (303 public and 1 private) from the validation analysis (Figure 1).
We checked for multicollinearity between county designation, employee type, and data submission technique using the Pearson correlation coefficient and found multicollinearity among public schools (p < 0.0001 for all) and none among private schools (County Designation vs. School Employee Type p = 0.27, County Designation vs. Data Submission Technique p = 0.77, Data Submission Technique vs. School Employee Type p = 0.10). Due to incomplete data and lack of resources for adequate follow-up, we did not include exemptions in the validation analysis. The variance of school district as a random effect was equal to zero, and not included in the final model. County designation, employee type, and data submission technique were tested for interaction; of which none was found. We found no significant association between a private school response with school size (p > 0.05) and county (p > 0.05); therefore, a weighted analysis was not pursued.
Our final model produced an adjusted absolute mean difference in proportion of kindergarten students who are up to date for all vaccines. Upon adjusting for school employee type, data submission technique, and county designation, vaccination data among public schools was overestimated by an absolute mean difference of 1.0% (92.1% school reported vs. 91.2% OSDH validated) and among private schools by an absolute mean difference of 3.3% (84.9% school reported vs. 80.0% OSDH validated; Table 2).
When evaluating school characteristics among public schools, we found that healthcare provider employee type and using the OSDH standardized template data submission technique impacted the reported vaccination coverage results by more than 10% (Table 3). Public schools that submitted school records in a customized report over-reported vaccination coverage by an absolute mean difference of more than twice as much as public schools that used the OSDH standardized template. In contrast, the county designation status (urban vs. rural) did not change the estimated mean difference in reported vaccination rates by more than 10%. Among private schools, no substantial changes in estimate were found when comparing school employee type, data submission technique, or county designation.
Thirty-four public schools, representing a total of 1,958 students were selected via a simple random sample for the audit of in-school student immunization records. These schools were selected from those that used the OSDH standardized template to submit data. Twenty-seven (79.4%) schools representing a total of 1,580 students voluntarily participated in the audit and provided redacted copies of their in-school student immunization records on file. The adjusted absolute mean difference in proportion of kindergarten students who are up to date for all vaccines was once again produced (Table 4). Upon adjusting for county designation and school employee type, school reported vaccination data was overestimated by an absolute mean difference of 0.6% compared to the true student immunization records on file examined during the audit. We found that neither school employee type nor county designation were significant predictors of the outcome.
Our analysis of the Oklahoma Kindergarten Vaccination Assessment indicates that school-reported vaccination data are sufficiently valid. We were reassured by the small degree of over-estimation reported by schools at an absolute mean difference of 3.3% among private schools and 1.0% among public schools. These results were further validated by the audit, which found public schools’ overestimation of vaccination coverage to be at an absolute mean difference of 0.6%. These findings are supported by studies which suggest similar variations in vaccination data via different data sources are acceptable (Fairbrother et al., 2000; Molinari et al., 2011; Stanwyck et al., 2007). To our knowledge, there is no established threshold to determine the validity of vaccination data, therefore, based on similar assessments of other public health data validity thresholds, an absolute mean difference of 3% was considered acceptable given available resources. Given these findings, we conclude that OSDH can rely on school self-reported vaccination data to take informed public health actions. We determine that there is not a need for OSDH to expend additional resources to further validate kindergarten assessments each year, while reserving the need to do so as new technology and survey methods are developed.
Albeit minimal, we found it useful to assess which school characteristics were driving factors in the adjusted absolute mean difference among public schools. We observed changes >10% in the accuracy of reporting vaccination data by school employee type and data submission technique. Healthcare staff were found to be the most accurate in reporting vaccination status which aligns with current evidence supporting the essential nature of these professionals in school health programs (Leidner et al., 2020; Salmon et al., 2004). In addition, schools that submitted records in a customized report exhibited twice the absolute mean difference in proportion of students up to date for all vaccines (−3.0%) as schools that submitted the OSDH standardized template (−1.4%). This may be an indication that schools submitting customized reports potentially faced challenges in interpreting student immunization records. This observation is consistent with other findings that school personnel face barriers in accurate assessment of vaccination requirements due to lack of time and resources (Limper et al., 2014; Salmon et al., 2004, 2006). While schools will be encouraged to submit student records to aid in correcting data entry errors, requiring submission on an annual basis would cause concerns for potential decrease in assessment participation.
This study had several limitations. First, our analysis was predominantly limited to self-reported vaccination data provided by schools; the OSDH standardized template only included fields to input the number of vaccine doses rather than the date of doses received to ensure minimum intervals were achieved. Second, we were unable to include private schools in the audit due to the difficulty in obtaining student vaccination records. Third, we were limited in our assessment of predictive school characteristics and nonresponse bias among private schools. Fourth, our analysis was challenged by exemption data due to widespread lack of data quality in school submissions. A lack of time and resources as well as the consideration of overburdening school systems prevented further follow-up to improve exemption data to include in the model. Fifth, the assessment of data reporting only included public and private school systems; therefore, these results are not generalizable to all school types, such as charter and homeschool programs. Sixth, we observed multicollinearity between school characteristics that could have led to unstable coefficient estimates and p-values generated by our model. Both the validation and audit models exhibited low coefficient of determinations near 2% and 1% respectively, which indicate a lack of predictive ability. The model may not reliably explain the variability in response data around the mean, and future studies should consider incorporating different and/or additional independent variables. Seventh, given that the model produced predicted values of absolute mean differences, confidence intervals could not be established for adjusted measures without the use of bootstrapping methodology.
Public health officials and policy makers will likely want to assess the impact the COVID-19 pandemic had on compliance with vaccination requirements for school entry. This study provides validated baseline data for compliance prior to the pandemic. Immunization record audits are helpful to assess differences in reporting of student vaccination data compiled by school employees versus public health experts. This study aids in providing guidance in the evaluation of data related to vaccine-preventable diseases as well as the assessment of immunization programs’ objectives in increasing vaccination coverage among children entering kindergarten.
This study highlights the importance of school-based healthcare personnel, i.e., school nurses in conducting basic functions related to public health infrastructure, including but not limited to health promotion and disease prevention, treatment of acute events, management of chronic conditions, and psychosocial support (Lineberry & Ickes, 2015). Studies demonstrate that school nurses have positive impacts on school systems from increased quality to higher attendance to cost savings (Lineberry & Ickes, 2015). For every $1 spent on school nursing, the community saves $2.20 (Wang et al., 2014). This study highlights the importance of school nurses in conducting basic functions related to public health infrastructure and the need to provide these professionals with additional resources and support.
It should be noted that while student vaccination data are valuable, recent uses of immunization registries and comprehensive immunization information systems have become more common in the United States (Trotter et al., 2021). Immunization registries are now capable of bi-directional communication between public health departments and clinicians (Trotter et al., 2021). Immunization registries also provide enhanced analytic capabilities that can aid in clinical decision support, vaccine ordering and inventory, and disease surveillance and outbreak responses (Trotter et al., 2021). Further investigation is needed to compare school electronic immunization systems with population-based immunization registries, both against each other and compared to patient medical records. Both public health departments and school systems stand to benefit from school nurses being given access to immunization registries to verify vaccine requirements and update records as needed.
Immunization record audits can provide confidence in the available data, which drives evidence-based decision-making. Local, retrospective school assessments work in conjunction with other methods to achieve a better understanding of true vaccination rates among the national cohort of children entering kindergarten each year. These results can also be used to track longitudinal trends in vaccine requirement exemptions to monitor the impact of growing vaccine hesitancy. Periodic immunization record audits and validation studies provide confidence in the accuracy and quality of vaccination data and maintain transparency in public health.
The author(s) declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.
The author(s) received no financial support for the research, authorship, and/or publication of this article
Ozair H. Naqvi https://orcid.org/0000-0001-8235-167X
Supplemental material for this article is available online.
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Ozair H. Naqvi, MS, is an epidemiologist in the Acute Disease Service of the Oklahoma State Department of Health and PhD student in the Department of Biostatistics and Epidemiology at the University of Oklahoma Hudson College of Public Health.
Aaron M. Wendelboe, PhD, MSPH is a professor of epidemiology at the University of Oklahoma Hudson College of Public Health.
Laurence Burnsed, MPH, MBA is an epidemiologist in the Acute Disease Service of the Oklahoma State Department of Health.
Mike Mannell, MPH is an epidemiologist in the Acute Disease Service of the Oklahoma State Department of Health.
Amanda Janitz, PhD, MPH is an assistant professor of epidemiology at the University of Oklahoma Hudson College of Public Health.
Stephanie Natt, BS is coordinator of exemptions, yellow fever, and vaccine support in the Immunization Service of the Oklahoma State Department of Health.
1 Acute Disease Service, The Oklahoma State Department of Health, Oklahoma City, OK, USA
2 Hudson College of Public Health, University of Oklahoma Health Sciences Center, Oklahoma City, OK, USA
Corresponding Author:Ozair H. Naqvi, The Oklahoma State Department of Health, Oklahoma City, OK 73104, USA.Email: Ozair-Naqvi@ouhsc.edu
