An Interrupted Time Series Multivariate Regression Analysis Evaluation of State Children's Health Insurance Programs (SCHIP) by Whitney Bowman-Zatzkin, MPA, MSR

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An Interrupted Time Series Multivariate Regression Analysis Evaluation of State Children's Health Insurance Programs (SCHIP) by Whitney Bowman-Zatzkin, MPA, MSR …

An Interrupted Time Series Multivariate Regression Analysis Evaluation of State Children's Health Insurance Programs (SCHIP) by Whitney Bowman-Zatzkin, MPA, MSR

As health insurance premiums continue to rise, the ability of many families to provide the critical health coverage to their children (both preventative and emergency) becomes an even greater challenge. In a study released in February 2005 in the Journal of Health Affairs, researchers found that half of those surveyed listed medical bills as the reason for their bankruptcy filings, with 75.7 percent of that half citing issues with health insurance during the illness resulting in the grandiose bills (Himmelstein, 2005). Figures released in 1997 from the Census Bureau reported a minimum of 10.7 million non-insured children within the United States (U.S. Bureau of the Census, 1997). The State Children’s Health Insurance Program (SCHIP) was developed to address these concerns.
SCHIP has been implemented as a supplemental Medicaid program for eligible children based on financial need. The original focus of SCHIP was to provide healthcare coverage to all children from birth to six years of age and having family incomes up to 133 percent of the Federal poverty level (FPL) while also covering children age six and over with family incomes at or above 100 percent of FPL. The goal was to have all children living below established poverty levels and under the age of 19 eligible for coverage by September 2002.
States could choose from the following implementation options.
1. Use SCHIP funding and expand their established Medicaid program to accommodate a larger percentage of children (Expansion Program).
2. Create a program for a new bracket of uninsured children, separate from Medicaid (New Program).
3. Combine the established Medicaid program with a new program offering separate enrollment options (Combination).
States are permitted to divert funds from other resources to provide healthcare to children under very loosely defined parameters. At the time, there was no children’s healthcare program with the strength and financial backing of SCHIP.
This paper evaluates the success of the SCHIP program and whether the choice of implementation design influences its success. SCHIP is currently under consideration for reauthorization making such an evaluation very timely. This paper proceeds as follows. First, I provide background about the SCHIP program. Next, I describe my research design and methods. Then I discuss my findings. Finally, I conclude with a discussion of my results.

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  • 1. UNIVERSITY OF CONNECTICUT AN EVALUATION OF STATE CHILDREN’S HEALTH INSURANCE PROGRAMS BY: S. WHITNEY R. BOWMAN-ZATZKIN Department of Public Policy June 2007
  • 2. 1 Introduction As health insurance premiums continue to rise, the ability of many families to provide the critical health coverage to their children (both preventative and emergency) becomes an even greater challenge. In a study released in February 2005 in the Journal of Health Affairs, researchers found that half of those surveyed listed medical bills as the reason for their bankruptcy filings, with 75.7 percent of that half citing issues with health insurance during the illness resulting in the grandiose bills (Himmelstein, 2005). Figures released in 1997 from the Census Bureau reported a minimum of 10.7 million non- insured children within the United States (U.S. Bureau of the Census, 1997). The State Children’s Health Insurance Program (SCHIP) was developed to address these concerns. SCHIP has been implemented as a supplemental Medicaid program for eligible children based on financial need. The original focus of SCHIP was to provide healthcare coverage to all children from birth to six years of age and having family incomes up to 133 percent of the Federal poverty level (FPL) while also covering children age six and over with family incomes at or above 100 percent of FPL. The goal was to have all children living below established poverty levels and under the age of 19 eligible for coverage by September 2002. States could choose from the following implementation options. 1. Use SCHIP funding and expand their established Medicaid program to accommodate a larger percentage of children (Expansion Program). 2. Create a program for a new bracket of uninsured children, separate from Medicaid (New Program).
  • 3. 2 3. Combine the established Medicaid program with a new program offering separate enrollment options (Combination). States are permitted to divert funds from other resources to provide healthcare to children under very loosely defined parameters. At the time, there was no children’s healthcare program with the strength and financial backing of SCHIP. This paper evaluates the success of the SCHIP program and whether the choice of implementation design influences its success. SCHIP is currently under consideration for reauthorization making such an evaluation very timely. This paper proceeds as follows. First, I provide background about the SCHIP program. Next, I describe my research design and methods. Then I discuss my findings. Finally, I conclude with a discussion of my results. Background Initially, with its new guidelines for eligibility, SCHIP performed as anticipated and the number of uninsured children experienced a decline between 1997 and 2001 from 9.9 million to 7.8 million (U.S. Department of Health and Human Services 2003, 26). In 1997, as many as 4 million uninsured children were eligible for Medicaid coverage but were most likely unaware they qualified for coverage (Richwine 2003). SCHIP included regulations about advertising both programs (Medicaid and SCHIP). Some states require that children be placed into Medicaid when they were eligible instead of placement within SCHIP.
  • 4. 3 After implementation there was an increase in SCHIP and Medicaid enrollment of all three program options while also showing a decline in the number of uninsured children (Smith 5). However, even with SCHIP, there were still 9 million uninsured children as of 2004 and infant mortality rates within the United States demonstrated an increase for the first time in 22 years (Wright-Edelman 5). The SCHIP program might have led to a decline in the health insurance offered by employers as shown in Table 1 (Gould 5). According to Gould (2004) the falling rate of private insurance might result in a larger pool of uninsured children eligible for SCHIP. Table 1 Employer-provided Health Insurance for Children Age 17 and Under, 2000-2003 Health Insurance Coverage (%) Change 2000 2001 2002 2003 2000-2003 All >18 65.60% 63.90% 63.00% 61.20% -4.40% Gould, Elise. 2004. “Employer Provided Health Insurance Falls for Third Consecutive Year.” Economic Policy Institute Brief #202. During its implementation, the federal government strongly endorsed the SCHIP program and provided supplemental funds to states on a graduated scale. At the time it was enacted, SCHIP was to receive $40 billion over its first ten years (U.S. Department of Health and Human Services 2003, 19). Once enacted, however, the program suffered from reduced funding. In 2004, however, a $1.1 billion surplus in federal funding to the SCHIP program had gone untouched due to state-level delays in program processes and enrollments (Wright-Edelman, 2004). Congress made legislative accommodations to allow these funds to be made available past the September 30, 2004 deadline (Wright- Edelman, 2004).
  • 5. 4 There has not been an evaluation of the SCHIP program that controls for exogenous factors that may influence enrollment in public health insurance. The Government Accountability Office (GAO) examined the SCHIP program in 2000. The GAO found that children’s enrollment in SCHIP/Medicaid health programs increased after SCHIP implementation. The welfare reform legislation that happened at the same time as SCHIP overhauled the methods for providing welfare services, linking together programs that had not been linked before, and breaking apart other channels of support. For example, applicants for a cash assistance or unemployment assistance also are likely to be told about health insurance assistance and other services. Joint applications have also been designed for multiple services. Thus, it is difficult to disentangle the welfare administrative changes from other program effects. In effect, the welfare changes might confound estimates of counterfactuals for evaluating the SCHIP program. Methods and Data This paper asks the following research questions: RQ1: Did SCHIP provide health insurance to more children? RQ2: Did the type of SCHIP implementation strategy make a difference in providing health insurance to children? In order to answer the above questions I test the following hypotheses: HØ 1 There is no difference in enrollment of children in public health insurance programs with SCHIP implementation. HA 1 SCHIP program implementation increases enrollment of children in public health insurance programs
  • 6. 5 HØ 2 There is no difference in enrollment of children in public health insurance programs with the type of SCHIP program implementation design. HA 2 Program implementation design will impact enrollment of children in public health insurance programs. The first hypothesis tests if SCHIP had an impact on the number of children enrolled in public health insurance. The second hypothesis tests whether program type matters in achieving the goals of SCHIP. This is a two-tailed test because program design could improve or reduce effectiveness I use an interrupted time series model to evaluate the effectiveness of SCHIP. Data was collected for all 50 states and Washington, DC for the years 1990 to 2004 from the Kaiser Family Foundation (SCHIP and Medicaid enrollment), the US Census Bureau (number of children in poverty), and the Bureau of Labor Statistics (Consumer Price Index). Enrollment figures for 1999 and 2004 are unavailable as of the time of this analysis. My causal models are as follows: Program Success (Enrollment) = ƒ{program implementation, number of children in poverty, consumer price index, state, year, state*year counter, e}; And, Program Success (Enrollment) = ƒ{program type , number of children in poverty, consumer price index, state, year, state*year counter, e}, Where, • Child Enrollment is defined as the number of children enrolled in SCHIP or Medicaid insurance programs. • SCHIP Program Implementation reflects the years each state did or did not have SCHIP implemented (1 if program is implemented, 0 if not).
  • 7. 6 • SCHIP Program Type is defined as the program selected by each state after the SCHIP implementation: No Program, Expansion Program, Combination Program and New Program. (Only one state had no program after the 1997 SCHIP implementation, and this was only in 2004) • Number of Children in Poverty controls for the pool of children potentially eligible for SCHIP. • Consumer Price Index controls for the price differences by region. • State controls for differences across states (specified as dummy variables representing each state). • Year controls for the differences by year (specified as dummy variables for each year). • State*Year Counter controls for the state specific linear time trends. Year Counter is defined as 1990=0, 1991=1 …2004= 14) • e is the model’s random error. The above model controls for the two important variables that might influence enrollment. The number of children in poverty controls for the pool of potentially eligible children. The regional consumer price index controls for price differences that might affect the cost of providing services. The model fixes the effects of state and year to control for unobserved variation across states and years. Finally, the model also controls for linear state specific time trends through the use of the State*Year Counter variable.
  • 8. 7 Findings After implementation of SCHIP, 28 percent chose a New Program design, 31 percent chose Expansion Program, and 41 percent chose Combination Program. Table 2 below shows the descriptive statistics. The number of enrolled children increased after program implementation and the percent of children in poverty fell. Table 2: Descriptive Statistics No Implementation Implementation Variable Mean Mean Change Number of Children Enrolled (In Thousands) 378 455 77 Percent of Children in Poverty 12 11 -1 Figure 1 below graphically shows the relationship between SCHIP/Medicaid enrollment and the percent of children in poverty. The figure indicates that while enrollment was increasing, the percent of children in poverty was decreasing. These figures do not control for state differences or within state time trends. However, the figure below underscores the need for the model to control for children in poverty.
  • 9. 8 Figure 1 Source: Enrollment: Kaiser Commission on Medicaid and the Uninsured and Urban Institute estimates based on data from HCFA-2082 and MSIS reports provided for this study by David Rousseau. Poverty: Accessed online through the U.S. Census Bureau at http://www.census.gov/hhes/www/saipe/tables.html Table 3 below shows the model results for all program implementation types. The results for the dummy variables for state, year, and the state*year counter interaction are not shown but are available upon request. The model suggests that enrollment increased after SCHIP implementation. The number of children enrolled in any form of SCHIP increased an average of 98,982 children with the program implementation (over the observed six years of program implementation). This is significant at the .05 level. The r-squared approaches unity, suggesting the model explains almost all of the variance in the dependent variable. Enrollment and % of Children in Poverty 10,000 12,000 14,000 16,000 18,000 20,000 22,000 24,000 26,000 28,000 30,000 1990 1991 1992 1993 1994 1995 1996 1997 1998 2000 2001 2002 2003 2004 Year Enrollmentand%ofChildreninPoverty 10 12 14 16 18 20 22 24
  • 10. 9 Table 3: Differences in Enrollment due to Program Implementation (All Types) Coefficient t-stat Significance Program Implementation 98.982 2.01 ** CPI -1.596 -0.61 Number of Children in Poverty 0.00087 21.34 *** R-squared 0.995 N 663 * = Significant at the .10 level ** = Significant at the .05 level *** = Significant at the .01 level Table 4 below shows the differences in enrollment due to the choice of program implementation type (again, state, year, and state*year counter not shown). All else equal, the number of children enrolled in SCHIP/Medicaid increases an average of 115,744 children with New program implementation. This finding is statistically significant at the .05 level. All else equal, the number of children enrolled in SCHIP/Medicaid increases an average of 96,228 with Expansion program implementation. Both New and Expanded programs were statistically significant at the .05 level. The point estimate for Combination program was not statistically significant.
  • 11. 10 Table 4: Differences in Enrollment due to Program Implementation Type Coefficient t-stat Significance New Program Implementation 115.744 2.27 ** Expanded Program Implementation 96.228 1.96 ** Combination Program Implementation 75.376 1.47 CPI -1.199 -0.46 Number of Children in Poverty 0.00087 21.34 *** R-squared 0.995 N 663 * = Significant at the .10 level ** = Significant at the .05 level *** = Significant at the .01 level An f-test indicates the point estimates for New and Combination program was statistically significantly different at the .01 level (f=6.83). There were no statistically significant differences between any of the other program types. Thus, the models suggest the following: • All else equal, SCHIP program implementation improved enrollment of children in public health care programs • All else equal, New and Expanded programs significantly improved enrollment of children in public health care programs • Although the point estimate is positive for Combination program, it was not statistically significant. • New program implementation improved enrollment more than Combination program. This result is significant at the .01 level.
  • 12. 11 Therefore, we reject the first null hypothesis and conclude that program implementation improved enrollment of children in public health care programs. The second hypothesis was that there is no difference in enrollment with the type of SCHIP program implementation design. There is strong evidence New program implementation performs better, in terms of increasing enrollment, when compared to Combination programs. Discussion Legislation and budget allocations for SCHIP are currently under consideration for renewal in Congress. My analysis demonstrates SCHIP improved the enrollment in children’s insurance programs and that New program implementation performs the best of the three options. My evaluation design improves upon existing SCHIP evaluations. I control for children in poverty, cost differences by region, unobserved variation by state and year, and linear time trends within states. No other evaluation employs such an extensive set of controls. The evaluation design provides comfort that the results accurately reflect SCHIP outcomes. However, despite the strengths of the evaluation design, it does not disentangle the potential impact of the overall welfare administrative changes from the influence of SCHIP implementation. Therefore, it remains possible that the increased enrollment after SCHIP implementation is due, in part, to the overall improvement in welfare program management that took place at exactly the same time. Careful state by state analysis of the impact of welfare reforms, such as increased numbers of referrals into SCHIP due to
  • 13. 12 changed administrative structures, would be necessary to separate the impact of SCHIP from welfare management changes. This analysis is beyond the scope of this paper. Enrollment in Medicaid and SCHIP programs is a good outcome variable in that it provides a measure of the change in the number of poor children enrolled in the program. However, the number of uninsured children in poverty would be a better measure because it would also include the potential effects of reduced private sector provided insurance. Future research using the number of uninsured poor children as the dependent variable would be welcome. Finally, I did not conduct a cost-benefit analysis so I must stop short of concluding that the enrollment increases due to SCHIP are worth the cost of implementing it. Further, the gains in enrollment for New program implementation may come at a commensurately higher cost. Future research that addresses the costs of SCHIP, as well as the benefits, would be an important addition to our understanding of this program.
  • 14. 13 References Cutler, David M. 1995. “The Cost and Financing of Health Care.” The American Economic Review 85:32-37. Dick, Andrew W., R. Andrew Allison, Susan G. Haber, Cindy Brach and Elizabeth Shenkman. 2001. “The Consequences of States’ Policies for SCHIP Disenrollment.” Agency for Healthcare Research and Quality Publications. Gould, Elise. 2004. “Employer Provided Health Insurance Falls for Third Consecutive Year.” Economic Policy Institute Brief #202. Gruber, Jonathan. 1997. “Policy Watch: Medicaid and Uninsured Women and Children.” The Journal of Economic Perspectives 11:199-208. Himmelstein, David U., and Elizabeth Warren, Deborah Thorne, and Steffie Woolhandler. 2005. “Illness and Injury as Contributors to Bankruptcy.” Journal of Health Affairs Report 63:1377-98. Kaiser Family Foundation. SCHIP Program Type by State. http://www.statehealthfacts. org/. Accessed March 3, 2007. Richwine, Lisa. 2003. “More U.S. Children Have Health Coverage.” Reuters Health, July. http://www.edenmedcenter.org/health/healthinfo/reutershome_top.cfm?fx =article&id =13166. Accessed June 22, 2007. Rousseau, David. Kaiser Commission on Medicaid and the Uninsured and Urban Institute estimates based on data from HCFA-2082 and MSIS reports. Provided on February 21, 2007. Shore-Sheppard, Lara D. 2000. “The Effect of Expanding Medicaid Eligibility on the Distribution of Children’s Health Insurance Coverage.” Industrial and Labor Relations Review 54: 59-77. Smith, Vernon. 2004. “SCHIP Program Enrollment, December 2003 Update.” Kaiser Commission on Medicaid and the Uninsured. January. U.S. Bureau of Labor Statistics. Consumer Price Index by Region. http://data.bls.gov/. Accessed March 3, 2007. U.S. Bureau of the Census. Current Population Reports, Series P60-202, September 1998. http://www.census.gov/hhes/www/hlthins/hlthin97/hlt97asc.html. Accessed February 22, 2007. U.S. Bureau of the Census. Small Area Income and Poverty Estimates. http://www.census.gov/ hhes/www/saipe/tables.html. Accessed March 3, 2007.
  • 15. 14 U.S. Congress. House. 1997. Balanced Budget Act of 1997. 106th Cong., 2d sess., H.R. 2015. U.S. Department of Commerce. General Accounting Office. 2000. Medicaid and SCHIP: Comparisons of Outreach, Enrollment Practices, and Benefits. Washington: GAO/HEHS-00-86. U.S. Department of Health and Human Services. Agency for Healthcare Research and Quality. 2002. SCHIP Disenrollment and State Policies. Washington: Department of Health and Human Services. U.S. Department of Health and Human Services. Office of the Assistant Secretary for Planning and Evaluation. 2003. Interim Evaluation Report: Congressionally Mandated Evaluation of the State Children’s Health Insurance Program. Washington: Department of Health and Human Services. Wright-Edelman, Marian. 2004. “Children's Health Jeopardized To Subsidize Special Interests,” Ethnic News, March.