UNIVERSITY OF CONNECTICUT

AN EVALUATION OF STATE CHILDREN’S HEALTH INSURANCE PROGRAMS

BY:

S. WHITNEY R. BOWMAN-ZATZKIN

Department of Public Policy

June 2007

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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).

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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.

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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).

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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

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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).

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• 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.

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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.

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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 2004Year

En

rollm

en

t an

d %

of

Ch

ild

ren

in

Po

vert

y

10

12

14

16

18

20

22

24

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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.

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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.

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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

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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.

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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.

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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.