Providing Web-based vaccine information with social media applications during pregnancy can positively influence parental vaccine behaviors.

Objective To describe parental vaccine decision making behaviors and characterize trust in physician advice among parents with varying childhood vaccination behaviors. Methods Between 2008 and 2011, a mixed methods study was conducted with parents of children aged <4 years who were members of Kaiser Permanente Colorado health plan. Seven focus groups were conducted with vaccine hesitant parents. Based on findings from the focus groups, a survey was developed, pilot tested and mailed to a stratified sample of 854 parents who accepted (n=500), delayed (n=227), or refused (n=127) vaccinations for one of their children. Survey results were analyzed using chi-square tests and multivariable logistic regression. Results Several themes emerged from the focus groups, including: 1) the vaccine decision making process begins prenatally, 2) vaccine decision making is an evolving process, and 3) there is overall trust in the pediatrician, but a lack of trust in the information they provided about vaccines. The survey response rate was 52% (n=443). Parents who refused or delayed vaccines were 2-times more likely to report that they began thinking about vaccines before their child was born, and 8-times more likely to report that they constantly re-evaluate their vaccine decisions than parents who accepted all vaccines. While parents tended to report trusting their pediatrician’s advice on nutrition, behavior and the physical examination, they did not believe their pediatrician provided balanced information on both the benefits and risks of vaccination. Conclusion These results have implications for future interventions to address parental vaccination concerns. Such interventions may be more effective if they are applied early (during pregnancy), often (pregnancy through infancy), and cover both the risks and benefits of vaccination.

OBJECTIVES To examine patterns and trends of undervaccination in children aged 2 to 24 months and to compare health care utilization rates between undervaccinated and age-appropriately vaccinated children. DESIGN Retrospective matched cohort study. SETTING Eight managed care organizations of the Vaccine Safety Datalink. PARTICIPANTS Children born between 2004 and 2008. MAIN EXPOSURE Immunization records were used to calculate the average number of days undervaccinated. Two matched cohorts were created: 1 with children who were undervaccinated for any reason and 1 with children who were undervaccinated because of parental choice. For both cohorts, undervaccinated children were matched to age-appropriately vaccinated children by birth date, managed care organization, and sex. MAIN OUTCOME MEASURES Rates of undervaccination, specific patterns of undervaccination, and health care utilization rates. RESULTS Of 323 247 children born between 2004 and 2008, 48.7% were undervaccinated for at least 1 day before age 24 months. The prevalence of undervaccination and specific patterns of undervaccination increased over time (P < .001). In a matched cohort analysis, undervaccinated children had lower outpatient visit rates compared with children who were age-appropriately vaccinated (incidence rate ratio [IRR], 0.89; 95% CI, 0.89- 0.90). In contrast, undervaccinated children had increased inpatient admission rates compared with age-appropriately vaccinated children (IRR, 1.21; 95% CI, 1.18-1.23). In a second matched cohort analysis, children who were undervaccinated because of parental choice had lower rates of outpatient visits (IRR, 0.94; 95% CI, 0.93-0.95) and emergency department encounters (IRR, 0.91; 95% CI, 0.88-0.94) than age-appropriately vaccinated children. CONCLUSIONS Undervaccination appears to be an increasing trend. Undervaccinated children appear to have different health care utilization patterns compared with age-appropriately vaccinated children.

No abstract

Among patients on chronic opioid therapy, the predictive model identified 66-82% of all subsequent opioid overdoses. This model is an efficient screening tool to identify patients who could benefit from naloxone to prevent overdose deaths. Population differences across the two sites limited calibration in the validation site.