Paediatric Infectious Diseases Fellow The Hospital for Sick Children Toronto, Ontario, Canada
Background: Vaccination is the best preventative measure against infectious diseases. However, there are still large gaps in immunizations amongst different populations, including in children who are at higher risk of complications from vaccine-preventable diseases. Sociodemographic factors are also associated with lower vaccine coverage, including higher index of remoteness and lower levels of education. Hospitalizations and clinic visits to tertiary care centres are a missed opportunity to identify gaps in routine immunizations and can thus play an important role in updating childhood vaccines. Objective: This project aims to utilize admission and clinic visits to a tertiary care pediatric centre to (1) Identify and understand gaps in childhood immunizations; (2) Identify barriers to vaccination; (3) Implement strategies to improve vaccine access and confidence; and (4) Facilitate increased uptake of immunizations. Design/Methods: We developed a quality improvement (QI) initiative that will take place on the paediatric wards at the Hospital for Sick Children from November 2023 to March 2024. The project is funded by the Public Health Agency of Canada and follows Plan-Do-Study-Act cycle methodology. Process, balancing and outcome measures were defined prior to the start of the project and QI approval was obtained. Baseline demographic information, immunization records, data on vaccine uptake, confidence, and family preferences for improving vaccination behaviours will be collected. Our team will recommend immunization strategies based on data collection, including: 1) Vaccinating in hospital; 2) Connecting patient to a vaccine clinic/family physician; 3) Referring to our Vaccine Call-in Line for further counseling or 4) Referring to our special immunization clinic. Data will be analyzed utilizing descriptive statistics, and characteristics of up-to-date versus under-immunized children will be compared using univariate statistics and multivariable logistic regression to identify factors associated with under-immunization.
