NoelleAngelique M. Molinari, PhD Nidhi Jain, MD CDC Human Papillomavirus Vaccine Initiation & Access to Care among US Teens, 2007 NoelleAngelique M. Molinari, PhD Nidhi Jain, MD CDC “The findings and conclusions in this presentation are those of the authors and do not necessarily represent the views of the Centers for Disease Control and Prevention.”

Background Advisory Committee on Immunization Practice recommended in June 2006 Quadrivalent vaccine (HPV) for females 3 dose series Aged 11-12 routine Aged 13-26 catch-up Costly $130.27 per dose (private sector cost to provider) * CDC cost = $100.59 * * CDC Vaccine Price List accessed 03/23/2009 www.cdc.gov/vaccines/programs/vfc/cdc-vac-price-list.htm

Objective Examine HPV initiation among female teens in US, 2007 Identify factors related to HPV initiation Income/Poverty status Health insurance Access to care Provider type Utilization

Data National Immunization Survey - Teen (NIS-Teen), 2007 RDD survey 4th Quarter National data only RDD survey CASRO* Response Rate ~ 56% Interview Completion ~ 84% Follow-up provider record check Provider Response Rate ~ 89% N = 1,441 females with provider-reported vaccine histories * Council of American Survey Research Organizations (CASRO) Response Rate = Resolution Rate * Screening Rate * Interview Completion Rate

Data Nationally representative sample of US teens aged 13 through 17 years Includes information on: Insurance status Parent- & provider-reported Well-child exams Vaccination coverage Demographics

Statistical Methods SUDAAN software used to calculate vaccine uptake Identify factors associated with HPV vaccine initiation Initiation is 1+ provider-reported HPV Bivariate tests of association: simple logistic regression Wald-F Chi-squared statistic Unadjusted odds ratios do not control for confounding

Results N = 1,441 71% 29%

Results ~ Bivariate Variables with No Evidence of Association (p > 0.15) Age Foreign born status Language of interview Mobility - moved since birth Teen’s grade in school Asthma diagnosis - proxy for health status Number of providers - scattering of care

Results ~ Bivariate Variables with Possible Association Census Region (p<0.001) Metropolitan Statistical Area (MSA) (p<0.001) Race/Ethnicity (p=0.12) Mother’s Education (p=0.01)

Results: Census Region Wald-F: p < 0.001 R E F N T OR = 0.5 p < 0.001 OR = 0.5 p < 0.001 OR = 0.6 p = 0.03

Results: MSA Wald-F: p < 0.001 R E F N T OR = 0.8 p = 0.11 OR = 0.5

Results: Race/Ethnicity Wald-F: p = 0.13 R E F N T OR = 1.4 p = 0.11 OR = 0.9 p = 0.7 OR = 0.6 p = 0.12

Results: Mother’s Education Wald-F: p = 0.01 OR = 1.2 p = 0.42 R E F N T OR = 0.9 p = 0.54 OR = 0.7 p = 0.14

Results ~ Bivariate Variables with Possible Association Access to Care Provider Type Facility Type Provider Specialty Utilization Parent-reported receipt of 11-12 yr Checkup Parent-reported # Visits in past 12 months (also proxy for health status) Household Income Health Insurance

Results: Facility Type Wald-F: p < 0.001 OR = 2.4 p = 0.00 OR = 2.4 p = 0.00 Mixed = public, private, R E F

Results: Provider Specialty Wald-F: p < 0.001 R E F N T OR = 0.9 p = 0.72 OR = 0.2 p = 0.00

Results: 11-12 Year Checkup Wald-F: p < 0.001 Provider contact  1+HPV coverage OR =2.0 p = 0.00 R E F N T

Results: # Visits past 12 months Wald-F: p < 0.001 As contacts rise 1+HPV coverage rises OR = 5.3 p = 0.00 OR = 4.7 p = 0.00 OR = 2.4 p = 0.01 R E F

Results: Health Insurance Wald-F: p < 0.001 As Out of Pocket (OOP) Price rises 1+HPV coverage falls OR = 1.2 p = 0.25 R E F N T OR = 0.3 p = 0.00

Results: Household Income Wald-F: p = 0.02 As Income rises 1+HPV coverage rises But note U-shape … OR = 1.6 p = 0.04 OR = 1.5 p = 0.13 R E F N T OR = 1.1 p = 0.77 OR = 0.8 p = 0.36

Summary Provider type may be important All public facilities  low coverage Other specialty provider  low coverage Utilization  high 1+HPV coverage Had checkup  higher coverage More provider contacts  higher coverage

Summary Insured  HPV initiation Income  HPV initiation Public has higher coverage than private Public insurance precedes private insurance Not insured  low coverage Price effect: high OOP HPV vaccine  low coverage Income  HPV initiation U-shaped relationship Un(der)insurance effect? Price effect? As income rises Lose access to public insurance Gain access to private insurance, but poor quality

Next steps… Add 2008 data – 4 more quarters Examine HPV coverage over time Multivariate model to adjust for Selection/ Simultaneity bias Provider type Utilization

Next steps… Examine relationship between insurance and utilization of care What factors affect insurance status? How does insurance influence access to care? Provider type Utilization

Thank You! NMolinari@cdc.gov