1. Improving Flu Vaccination Rates for Children with Chronic Conditions
CHEAR Unit, Division of General Pediatrics, University of Michigan
Improving Flu Vaccination Rates for Children with Chronic Conditions
Kevin Dombkowski, DrPH, MS
April 20, 2010

2. Guiding Questions How accurate is the MCIR high risk indicator?
How effective is this indicator for improving flu vaccination rates among children with chronic conditions?

3. MCIR High Risk Indicator
Accuracy of MCIR high risk indicator was assessed via parent telephone interviews:
physician diagnosis of asthma
asthma symptoms, medications and health services use
activity limitations
Interviews conducted:
March – June, 2008
February – May, 2009

4. MCIR High Risk Indicator
Overall, 89% confirmed asthma or similar condition:
asthma: 83%
wheezy cough: 5%
reactive airway disease (RAD): 1%

5. Objective
To assess the effectiveness of seasonal influenza vaccination reminder notices for children with high risk conditions using a statewide IIS

6. Methods Used the Michigan Care Improvement Registry (MCIR)
Pilot tested reminders in 3 local health departments:
Kent
Kalamazoo
Ottawa
Identified 3,618 high risk children months (October, 2008)

8. Methods Randomized into two groups: Reminders: Mailed reminders
No reminders
Reminders:
mailed November, 2008
sent via First Class USPS mail, marked “return service requested”

9. Methods
Determined validity / accuracy of mailing addresses using the US Postal Service National Change of Address (NCOA) process
Classified as undeliverable:
Invalid addresses
COA >1 year prior to notification date
COA identifies out-of-state move

10. Methods Assessed flu vaccination: Primary outcomes assessed:
Oct – Feb. 2009
Primary outcomes assessed:
Flu vaccination status
Time until flu vaccination
Used MCIR and Medicaid claims
Assessed bivariate and multivariate associations

11. Study Sample

20. Flu Vaccination Results

24. Flu Vaccination Child Characteristics n (1,946) Flu Vaccine %
Age (months)
24-35
630 28
36-47
669 26
48-59
647
Crude association between age and shot after notification using logistic regression:
24-35 mo: Reference
36-47 mo: OR = 0.9, p = 0.8
48-59 mo: OR= 9.3, p = 0.7

25. Flu Vaccination Child Characteristics n (1,946) Flu Vaccine %
Race/Ethnicity
White
975 25
Black
497 24
Hispanic
373 34
All others
101 26
Crude association of race and shot after notification (Y/N) using logistic regression:
White = Reference
Black OR = 1.0, p = 0.1
Hispanic OR = 1.6, p = 0.001
Other OR = 1.0, p = 0.7

26. Flu Vaccination Child Characteristics n (1,946) Flu Vaccine %
Flu Vaccine in
Previous Season
Yes
1223 30 No
723 21
Crude association between flu vaccination in previous season (y/n) and shot after notification (y/n) using logistic regression:
Yes: OR =1.67, p=<0.0001
No: Reference

27. Flu Vaccination Child Characteristics n (1,946) Flu Vaccine %
Medicaid Enrollment in October 2008
Yes
1711 28 No
235 17
Crude association between Medicaid enrollee in October 2008 (y/n) and shot after notification (y/n) using logistic regression:
Yes: OR =1.94, p=<0.0001
No: Reference

28. Cumulative Immunization (n=2552)

29. Cumulative Immunization (n=2552)

30. Cumulative Immunization (n=2552)

31. Cumulative Immunization (n=2552)

32. Cumulative Immunization (n=2552)

33. Cumulative Immunization (n=2552)

34. Notification
Mailed notification was associated with earlier immunization, controlling for:
age
race/ethnicity
history of flu vaccination
Medicaid enrollment
Undeliverable notices have a negative impact on flu vaccination rates
Multivariate modeling methods in SAS:
*TPHREG
*Cox-proportional hazards
*Modeled time until 1st shot, censored shot after notification (y/n)
Notification: HR = 1.22, p = 0.03
Influenza Vaccination in Any Previous Year: HR =1.54, p =<0.0001
Medicaid Enrollment in October 2008 : HR=1.82, p=0.0003
Race/ethnicity: Black: HR =0.94, p= 0.58
Race/ethnicity: Hispanic: HR=1.39, p=0.003
Race/ethnicity: Other or Unknown: HR=1.12, p=0.58

35. Impact of Undeliverable Notices

36. 29%
24%

37. 30%
23%

38. Limitations Pilot implementation in 3 LHD jurisdictions
Implementation varied between LHDs, including format of message

39. Conclusions
It is feasible to target reminders for seasonal flu vaccination using a statewide IIS
Seasonal flu vaccination rates among children with high risk conditions were substantially higher than historical rates

40. Conclusions
Reminder notices from the local health department were associated with a modest increase in seasonal flu vaccination
Improved reminder deliverability could be achieved by address corrections prior to mailing

41. Implications
Targeted reminder notices to children with chronic conditions may be effective mechanism to increase seasonal flu vaccination rates
Improved parent contact information may lead to increased effectiveness of seasonal flu vaccination reminder programs

42. What if a Shortage Occurs?
May be especially important to identify priority cases when flu vaccine supplies are limited

43. Acknowledgements Many thanks to my collaborators at:
University of Michigan
Michigan Dept. of Community Health
Michigan Care Improvement Registry
Kalamazoo, Kent and Ottawa County Health Departments
Centers for Disease Control and Prevention

44. Thank you for your attention!