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Published on: August 7, 2017
Identifying factors predicting immunization delay for children followed in an urban primary care network using an
Alexander G Fiks1, Evaline A Alessandrini, Anthony A Luberti
1Pediatric Research Consortium, Children's Hospital of Philadelphia, Philadelphia, PA 19104, USA. fiks@email.chop.edu
Insights
Early immunization status is a key predictor of childhood immunization delay. Electronic health records can help identify at-risk children as early as 3 months for timely intervention.
Area of Science:
- Public Health
- Pediatrics
- Health Informatics
Background:
- Electronic health records (EHRs) offer a valuable resource for collecting comprehensive patient data.
- Utilizing EHRs can streamline the assessment of immunization status and identify barriers to timely vaccination.
Purpose of the Study:
- To identify factors associated with immunization delay in young children using point-of-care EHR data.
- To assess the utility of EHRs in predicting and potentially mitigating immunization delays.
Main Methods:
- A retrospective cohort study analyzed data from 5464 children aged 2-5 years.
- Electronic health record data were used to evaluate demographic, clinical, and immunization variables.
- Univariate and multivariable models predicted immunization delay at 24 months according to Advisory Committee on Immunization Practices guidelines.
Main Results:
- Inadequate immunization at 3 months was the strongest predictor, with affected children being over 4.5 times more likely to be delayed at 24 months.
- Insurance status and non-parental caregiver were associated with increased immunization delay.
- Premature birth was associated with a lower likelihood of immunization delay.
Conclusions:
- Early immunization status, identifiable by 3 months, is a strong predictor of subsequent immunization delay in children.
- Electronic health records are a practical tool for identifying high-risk children and informing interventions to improve immunization rates.
Objective:
An opportunity exists to use increasingly prevalent electronic health records to efficiently gather immunization, clinical, and demographic data to assess and subsequently reduce barriers to immunization. The objective of this study was to use data entered at the point of care within an electronic health record to identify factors that predispose children in an inner-city population to immunization delay.
Methods:
Retrospective cohort data from an electronic health record were used to evaluate the association between demographic, clinical, and immunization variables on immunization delay at 24 months. Patients 2 to 5 years old as of May 31, 2003, with an office visit between May 31, 2002, and May 31, 2003, were selected (N = 5464). Univariate and multivariable models were developed to predict vaccination delay at 24 months per the Advisory Committee on Immunization Practices guidelines.
Results:
Overall up-to-date immunization rates at 3, 7, 13, and 24 months were 75%, 45%, 82%, and 71%. Multivariable models using electronic health record data showed that early immunization status was the strongest predictor of immunization delay at 24 months. Multivariate analysis revealed that children who were inadequately immunized at 3 months of age were more than 4.5 times as likely to be immunization delayed at 24 months. In this analysis, patient and caregiver factors associated with immunization delay included insurance status and nonparent caregiver. Children who were premature were less likely to be delayed.
Conclusions:
Using an electronic health record with information entered at the point of care, we found that early immunization status is a strong predictor of immunization delay for young children that can be identified as early as 3 months of age. Electronic health records may prove useful to clinicians and health systems in identifying children at high risk for immunization delay.
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