Elements of Influenza Vaccination Programs That Predict Higher Vaccination Rates: Results of an Emerging Infections Network Survey
Introduction. To address suboptimal influenza vaccination rates among health care workers, the Healthcare Infection Control Practices Advisory Committee and the Advisory Committee on Immunization Practices recently issued recommendations designed to increase the number of health care workers vaccina...
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Veröffentlicht in: | Clinical infectious diseases 2008-01, Vol.46 (1), p.14-19 |
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Sprache: | eng |
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Zusammenfassung: | Introduction. To address suboptimal influenza vaccination rates among health care workers, the Healthcare Infection Control Practices Advisory Committee and the Advisory Committee on Immunization Practices recently issued recommendations designed to increase the number of health care workers vaccinated against influenza. The purpose of the present study was to determine how widely these recommendations have been implemented and to identify important elements of successful influenza vaccine programs. Methods. The Infectious Diseases Society of America Emerging Infections Network surveyed 991 infectious diseases consultants. Infectious diseases consultants were asked about vaccination programs and vaccination rates at their respective institutions. Multinomial logistic regression models based on proportional odds were used to determine predictors of vaccination‐rate categories. All program elements were significant univariable factors in predicting vaccination rates. Because the program elements were highly associated with one another, principal components analysis was used to find combinations of the covariates that would serve as optimal predictors of higher vaccination rates. Results. Most infectious diseases consultants indicated that the vaccination rate for all health care workers in their institution had a range of 41%–60%. Vaccination rates were significantly higher in institutions that required signed declination statements (P=.004). In the model based on principal components analysis for predicting institutional vaccination rates, only the first principal component warranted retention (P |
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ISSN: | 1058-4838 1537-6591 |
DOI: | 10.1086/523586 |