Preventive Service Utilization by Minnesota Children

1. Preventive Service Utilization by Minnesota Children Minnesota Health Services Research Conference January 26, 2004 April Todd-Malmlov Health Economics Program Minnesota Department of Health

2. Background: Cover All Kids (CAK) • In early 2001, the Cover All Kids Coalition was formed to promote health care coverage and preventive care for MN children. • The Coalition is comprised of various public and private partners including: • MN Dept of Health - MHHP (now MHA) • MN Dept of Human Services - Neighborhood Health Care Network • Children’s Defense Fund - MN Community Action Association • Academy of Pediatrics-MN - Minneapolis Healthy Learners Board • MN Council of Health Plans - Legal Services Advocacy Project • MMA - Joint Religious Legislative Coalition • MNA - Congregations Concerned for Children • Nat’l Assoc. of Pediatric NPs & - MPHA Associates 2

3. Background: Information Needs • In order to measure progress towards the Coalition’s goals of increasing health insurance coverage and use of preventive services for children, baseline information was needed for all children in the state. • No State level survey exists that measures health insurance coverage and use of preventive services for all children in Minnesota: • MN Health Access Survey provides information on health insurance for all MN children, but not preventive services. • HEDIS provides information on preventive services for certain age groups of children enrolled in HMOs or public health insurance programs. Only provides information for 30-40% of children in MN – ignores children with commercial health insurance, self insured employer coverage, and children who are uninsured. 3

4. Background: CAK and BRFSS • In 2001, CAK worked with the MN Department of Health to add questions to the 2002 Behavioral Risk Factor Surveillance System (BRFSS) for children. • Questions in the BRFSS Child Health Module provide information on health insurance, dental coverage, well child visits, and dental visits for a random sample of children ages 0 through 17. Data provided allows for detailed analysis of factors related to preventive service utilization. • The Child Health Module was funded by MDH, DHS, the MN Council of Health Plans, and the St. Paul-Ramsey County Dept of Public Health. 4

5. Background: Relationship to Prior Research • Many studies have looked at the relationships between demographics, insurance status and health care utilization in general for children (Flores et al 1999; Newacheck et al 1998; Newacheck, Hughes, and Stoddard 1996; Short and Lefkowitz 1992). • Some studies have looked at the impact of parent and child characteristics on general health care utilization for children (Davidoff et al 2003; Hanson 1998; Newacheck and Halfon 1986). 5

6. Background: Relationship to Prior Research (Continued) • Other studies have looked at the impact of parent and child characteristics on preventive service utilization by children (Davidoff et al 2003; Bates et al 1994; Byrd, Hoekelman, and Auinger 1999; Ronsaville and Hakim 2000; Yu et al 2002). • However, these prior studies that have looked at the impact of various factors on preventive service utilization for children are limited in scope. No study has included all of the following: • various parent, child, and household characteristics • all children, regardless of age, insurance status, or income • well child visit guidelines as opposed to at least one visit 6

7. Research Questions • What percentage of Minnesota children are meeting various well child visit frequency guidelines? • What percentage of Minnesota children over age three had at least one dental visit in the past year? • What are the characteristics of children who did not meet well child visit guidelines or did not have a dental visit? • What is the impact of various parent, child, and household characteristics on whether or not children met well child visit guidelines or had a dental visit? 7

8. Methods: Data Source • The BRFSS is a collaborative telephone survey conducted by the states and CDC. • The BRFSS is designed to measure behavioral health issues and risk factors in the adult population over the age of 18. • All states ask a certain set of questions in order for the data to be comparable from state to state; however, states have some flexibility in adding their own questions. • In Minnesota, the BRFSS is conducted by the Center for Health Statistics at the Minnesota Department of Health. 8

9. Methods: Data Source (Continued) • The questions in the Child Health Module added to the 2002 MN BRFSS were asked of all adult respondents who reported that there were children in the household. • The adult respondent was asked to respond to the Child Health Module questions for one randomly selected child in the household. • In 2002, 4500 adults responded to the MN BRFSS and the interview completion rate was 88%. • Of the 4500 adults responding, 1600 completed the Child Health Module or 99% of adult respondents reporting children in the household. 9

10. Methods: Data Source (Continued) • Due to the length of time allotted for the Child Health Module, questions related to race/ethnicity, geography, household income, and family composition were not asked directly of the child or of the adult respondent on behalf of the child. The analyses assume that the responses of the adult to these questions also apply to the child. • In addition to data collected through the Child Health Module, data relating to household characteristics and parental demographics, health care access, utilization, and coverage from the BRFSS was used in the analyses. 10

11. Methods: Data Source (Continued) • The analyses assume that the adult respondent is a parent of the randomly selected child. • Some adult responses were eliminated from the analyses comparing adults and children. In instances where the age of the child and the age of the adult suggest that the adult is not the parent of the child, the responses of the adult to some demographic, family composition, health insurance, dental coverage, and health care utilization questions were eliminated. • The responses of approximately 80 adults were dropped from the descriptive and regression analyses. 11

12. Methods: Descriptive Statistics • The American Academy of Pediatrics (AAP), Child and Teen Checkup (C&TC), and the Institute for Clinical Systems Improvement (ICSI) guidelines are all used to analyze the percent of children in Minnesota who met well child visit frequency guidelines in 2002. • Children were classified as meeting the well child visit frequency guidelines if they received the recommended number of well child visits in the past year(s) based on their age (in months for children under age two). The survey did not attempt to assess whether all of the recommended services were provided during the well child visits reported by parents. 12

13. Methods: Descriptive Statistics (Continued) • Due to question wording, an exact estimate of children meeting ICSI guidelines is not possible. It is assumed that a child over the age of two meets ICSI guidelines if they had a well child visit in the past two years. This assumption may underestimate those meeting ICSI guidelines. • Question wording does not allow for an analysis of children meeting dental guidelines. It only allows for an analysis of children having at least one dental visit in the past year. • The data was analyzed using Stata survey commands to account for complex survey design and weighting. 13

14. Methods: Logistic Regression • Logistic regression is used to quantify the relative impact of various parent, child, and household characteristics on dental and well child visit utilization. • The dependent variables include: • Whether or not children age three or older had a dental visit in the past year • Whether or not children met the C&TC or ICSI well child visit frequency guidelines – C&TC guidelines are applied to uninsured children and those with public coverage and ICSI guidelines are applied to children with private coverage. 14

15. Methods: Logistic Regression (Continued) • Conceptual Framework: Aday and Anderson’s model of health services utilization (1974, 1981). Dental and well child visit utilization are modeled as a function of predisposing, enabling, need, and availability factors. • Analyses were conducted using svylogit commands to account for complex survey design and weighting. • Odds ratios are reported for the logistic regression analyses. 15

16. Methods: Logistic Regression (Continued) • Interactions between parent and child dental coverage and parent and child health insurance coverage were detected. • To deal with these interactions and account for the importance of coverage for both parents and children, three logistic regression models were conducted for both dental and well child utilization: • One model was constructed including coverage for parents and children to obtain odds ratios for other variables in the model excluding parent and child coverage. • In a second model, an odds ratio for parental coverage was derived by excluding child coverage from the model. • In a third model, an odds ratio for child coverage was derived by excluding parental coverage from the model. 16

17. Methods: Independent Variables in Dental and Well Child Models 17

18. Results: Percent of Children 3+ With Dental Visit in Past Year *Indicates statistically significant difference (90% level) from all children **Indicates statistically significant difference (90% level) from White, Non-Hispanic 18

19. Results: Characteristics of Children With and Without a Dental Visit *Indicates statistically significant difference (90% level) from children who had a dental visit 19

20. Results: Percent of Children Meeting Well Child Visit Guidelines *Indicates statistically significant difference (90% level) from all children **Indicates statistically significant difference (90% level) from White, Non-Hispanic ***Indicates statistically significant difference (90% level) from Greater MN 20

21. Results: Characteristics of Children Who Did and Did Not Meet Well Child Guidelines *Indicates statistically significant difference (90% level) from children who met guidelines 21

22. Results: Logistic Regression Dental Visit Model 22

23. Results: Logistic Regression Well Child Visit Guideline Model 23

24. Conclusions • Over 87% of Minnesota children ages three or older had at least one dental visit in the past year. • Depending on the guideline, roughly 72% to 83% of MN children met well child visit guidelines in 2002. • A child’s age, parental dental care, household income, and type of child and parental dental coverage had a greater impact on dental utilization than other factors. • A child’s age, parental and child health coverage, household income, parental age, continuity of care, and geography had a greater impact on meeting well child visit guidelines than other factors. 24

25. Conclusions (Continued) • Similar themes for dental and well child utilization: • Younger children and children of young parents were less likely to have a dental visit or meet well child guidelines • Insurance coverage for parents and children is associated with having a dental visit and meeting well child guidelines • Different themes for dental and well child utilization: • Income: higher income important factor for dental visit and lower income important factor for meeting well child visit guidelines • Geography: no impact for dental visit, but Twin Cities location important factor for meeting well child visit guidelines • Parental preventive actions: important for dental visit, but not important for meeting well child visit guidelines 25

26. Limitations and Future Work • Limitations: • Health status not asked of children in Child Health Module • Type of insurance coverage for adults not asked on BRFSS • Self-reported information from parents • Limitations mentioned earlier regarding question wording and assumptions of parent and child characteristics • Future Work: • Rewording of some questions in Child Health Module • Addition of some questions to Child Health Module • More research on the impact of geography and parental preventive actions on use of preventive care by children. • SLAITS National Survey of Children’s Health: • Similar questions to 2002 MN BRFSS Child Health Module • Data collected during 2003 and available sometime in 2004 • 2000 sample size per state 26

27. Take Home Message • Various strategies in addition to increasing insurance coverage for children, could potentially increase the use of preventive services for Minnesota children. Other strategies include: • Improving continuity of care for children • Increasing preventive service utilization and insurance coverage for parents • Increasing outreach efforts in Greater MN and for young parents with young children • Outreach efforts may be more effective and easier for providers and parents to understand and remember if one set of guidelines is used for all kids 27