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Appendix D
Recent Studies of the Impacts of Health Insurance for Children: Summary Tables
Five tables summarizing the evidence since 2002 on the impacts of health insurance for children are presented in this appendix. These tables were originally presented in a literature review commissioned by the Institute of Medicine Committee on Health Insurance Status and Its Consequences in 2008 titled Health and Access Consequences of Uninsurance Among Children in the United States: An Update, by Genevieve M. Kenney, Ph.D., and Embry Howell, Ph.D., The Urban Institute.
Table D-1: General Health Care: Impacts of Health Insurance on Children’s Access and Use of Care
Table D-2: Dental Services: Impacts of Health Insurance on Children’s Access and Use of Dental Services
Table D-3: Immunizations: Impacts of Health Insurance on Children’s Immunizations
Table D-4: Impacts of Health Insurance on Special Populations of Children
Table D-5: Impacts of Health Insurance on Children’s Health Status and Related Outcomes
Several abbreviations are used frequently in the tables:
ACSC = ambulatory care sensitive condition
ADHD = Attention Deficit Hyperactivity Disorder
CHI = children’s health initiatives
CSHCN = children with special health care needs
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D-D = difference-in-difference
IR = incidence ratio
MEPS = Medical Expenditure Panel Survey
NHANES = National Health and Nutrition Examination Survey
NHIS = National Health Interview Survey
NSAF = National Survey of America’s Families
NSCH = National Survey of Children’s Health
OLS = ordinary least squares
Rx = prescription
SCHIP = State Children’s Health Insurance Program
Changes are statistically significant unless otherwise noted as “not significant” (“NS”). N/A indicates that the study in question did not examine the specified outcome.
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TABLE D-1 General Health Care: Impacts of Health Insurance on Children’s Access and Use of Care
Citation
Location and Time Period of Analysis
Data Sources
Methodology
National Studies
Banthin and Selden (2003)
The ABCs of children’s health care: How the Medicaid expansions affected access, burdens, and coverage between 1987 and 1996
United States, 1987 and 1996
National Medical Expenditure Survey (1987) and MEPS (1996)
D-D approach: change between 1987 and 1996 for poverty-related children less change over same time period for slightly higher-income children: Children made eligible for Medicaid under the poverty-related expansions in the 1980s are the treatment group and children with slightly higher income levels—defined as those in the income groups ultimately made eligible for SCHIP as of 2000—are the primary comparison group; controls included a variety of sociodemographic characteristics, as well as income and health status. Service use refers to previous 12 months.
Currie et al. (2008)
Has public health insurance for older children reduced disparities in access to care and health outcomes?
United States, 1986 to 2005
NHIS (N = 548,789)
Examine impacts of Medicaid/SCHIP eligibility expansions on probability of an ambulatory visit and reported health status using a simulated eligibility indicator to address potential endogenity of eligibility. Medicaid/SCHIP generosity index generated by applying state eligibility rules to a sample of children for each state and year. Control variables include interaction terms and age and year dummies. Look at concurrent and lagged effects. Still potentially biased and concerns about appropriateness of simulated eligibility measure in studies of all kids. Service use refers to previous 12 months.
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Findings
Usual Source of Care
Any Ambulatory Visit
Any Preventive Visit
Any Unmet Need
Specific Unmet Needs
2.1 percentage point increase (NS)
9.3 percentage point increase
N/A
N/A
N/A
N/A
Eligible children 6.8 percentage points more likely to have ambulatory visit in past year; children ages 9-17 who were eligible as younger children are 3.9 to 8.9 percentage points more likely to have doctor’s visit; find positive lagged eligibility effects
N/A
N/A
N/A
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Citation
Location and Time Period of Analysis
Data Sources
Methodology
Davidoff et al. (2005)
Effects of the State Children’s Health Insurance Program expansions on children with chronic health conditions
United States, 1997, 2000, 2001
NHIS core data source supplemented with state data on policy changes, local data on private premiums
D-D approach: two treatment groups—children in the income group made newly eligible under SCHIP and children already eligible for Medicaid under the poverty-related expansions; comparison group: children with incomes slightly above the SCHIP eligibility thresholds; wide-ranging control variables to address possible confounding changes occurring over the same period. Service use refers to previous 12 months. Sample is restricted to children with chronic health conditions.
Selden and Hudson (2006)
Access to care and utilization among children: Estimating the effects of public and private coverage
United States, 1996-2002
MEPS supplemented with state-level Medicaid/SCHIP eligibility and private premiums information; N = 49,003
Children uninsured for full year compared to children with private coverage only and to children with any public coverage. Two-stage least squares with instrumental variables used to address selection bias (estimates reported here are from the model using family instruments). Found that OLS estimates understate positive effects of coverage. Service use refers to previous 12 months.
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Findings
Usual Source of Care
Any Ambulatory Visit
Any Preventive Visit
Any Unmet Need
Specific Unmet Needs
N/A
2.4 percentage point increase (NS)
N/A
8.6 percentage point decrease
Rx: 3.7 percentage point decrease
38.5 (public) and 39.7 (private) percentage points more likely than uninsured
32.7 (public) and 30.1 (private) percentage points more likely than uninsured
33.5 (public) and 26.8 (private) percentage points more likely to comply with well-visit guidelines
N/A
N/A
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Citation
Location and Time Period of Analysis
Data Sources
Methodology
State Studies
Damiano et al. (2003)
The impact of the Iowa S-SCHIP program on access, health status, and family environment
Iowa, 1999-2000
Two-wave mail survey (with telephone followup) of parents of new enrollees in Hawk-I (SCHIP) and 1 year later; (N = 463) response rate = 80% for baseline and 72% for followup
Pre-post cohort/longitudinal design. Outcomes for new enrollees compared to outcomes for the same enrollees 1 year later; no information provided on prior coverage of new enrollees. Service use refers to previous 12 months.
Dick et al. (2004)
SCHIP’s impact in three states: How do the most vulnerable children fare?
Kansas, Florida, and New York. Baseline between June 2000 and March 2001; Followup interviews were conducted 1 year later
Surveys of enrollees in State Children’s Health Insurance Programs; adolescents only in FL.
KS: N = 434, response rate = 35% FL: N = 944, response rate = 30% NY: N = 2,290, response rate = 55%
Pre-post cohort/longitudinal design. Included children who had disenrolled from SCHIP. Provide separate estimates for children who were previously uninsured.
Feinberg et al. (2002)
Family income and the impact of a children’s health insurance program on reported need for health services and unmet health need
Massachusetts, 1998-1999
One-wave telephone survey of parents of children in enrolled in Mass. Children’s Medical Security Plan, a precursor to SCHIP, that included children of all incomes. (N = 877 primary sample plus 119 Spanish oversample); response rate = 62%
Compared experiences of children before and after enrollment, which parents were asked to recall.
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Findings
Usual Source of Care
Any Ambulatory Visit
Any Preventive Visit
Any Unmet Need
Specific Unmet Needs
Increased from 81% to 89%
N/A
N/A
Decreased from 27% to 9% (medical need)
Specialty: Decreased from 40% to 13%; Vision: Decreased from 46% to 12%; Behavioral/Emotional: Decreased from 42% to 18%; Rx: Decreased from 21% to 13%
NY: Increased from 78% to 97%
N/A
KS: Increased from 51% to 66% (NS); NY: increased from 67% to 80%
KS: Decreased from 53% to 20%; NY: decreased from 32% to 21%
N/A
N/A
N/A
N/A
Excluding dental: Declined from 12% before enrollment to 7% after
Rx: Declined from 4% to 3%; Vision: Declined from 30% to 17% (NS); Mental: Declined from 33% to 17% (NS)
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Citation
Location and Time Period of Analysis
Data Sources
Methodology
Fox et al. (2003)
Changes in reported health status and unmet need for children enrolling in the Kansas children’s health insurance program
Kansas, 1999-2000
Two-wave survey of parents of children enrolled in the program in its first 6 months and of the same parents 1 year later; (N = 1,955), response rate = 60% (Wave 2)
Pre-post cohort/longitudinal design. Responses for children just after enrollment compared to responses for same children 1 year later. Service use refers to previous 12 months.
Kempe et al. (2005)
Changes in access, utilization, and quality of care after enrollment into a state child health insurance plan
Colorado, 1999-2001
Survey of enrollees in Colorado’s Child Health Plus Program; Baseline survey during 1999 and 2000; follow up survey 1 year later. (N = 480). Response rate = 77% for baseline and 68% for followup
Pre-post cohort/longitudinal design, controlling for race/ethnicity, age, prior insurance status; no separate results reported for the kids who had been uninsured prior to enrolling in SCHIP. Report IR for post- versus pre-enrollment.
Kenney (2007)
The impacts of the state children’s health insurance program on children who enroll: Findings from 10 states
10 states (CA, CO, FL, IL, LA, MO, NC, NJ, NY, TX), 2002
One-wave survey of parents of children newly enrolled in SCHIP or enrolled for 1 year; response rate = 75-80% depending on state; N = 16,700; data pooled across states. Primary sample consists of 5,394 established enrollees and 3,106 recent enrollees
Compare pre-SCHIP experiences of uninsured children to SCHIP experiences of SCHIP enrollees; regression adjustment for demographic characteristics and income; sensitivity analyses to examine selection. Service use refers to previous 6 months.
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Findings
Usual Source of Care
Any Ambulatory Visit
Any Preventive Visit
Any Unmet Need
Specific Unmet Needs
Increased from 91.9% to 95.6%
N/A
Increased from 60.5% to 76.7%
Share who received all care needed increased from 48.9% to 83.5%
Mental health: Decreased from 4.2% to 1.1%; Vision: Decreased from 17.0% to 4.0%; Rx: Decreased from 14.1% to 2.3%
Usual source of preventive care IR = 1.02 (NS)
N/A
Routine visit: IR = 1.39
N/A
Rx: IR = .38; Mental: IR = .63; Dental: IR = .59; Routine care: IR = .17; Sick care: IR = .27; Eyeglasses: IR = .44
21 percentage point increase
7 percentage points increase
11 percentage point increase
13 percentage point decrease
Rx: 6 percentage point decrease; Specialist: 6 percentage point decrease; Hospital care: 6 percentage point decrease
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Citation
Place and Time Period of Findings
Data Sources
Yu et al. (2006)
Role of SCHIP in serving children with special health care needs
United States, 2001
National Survey of Children with Special Health Care Needs (N = 38,866)
NOTE: Changes are statistically significant unless otherwise noted as “not significant” (“NS”). N/A indicates the study did not examine that outcome. CHSCN = children with special health care needs; MEPS = Medical Expenditure Panel Survey; NHIS = National Health Interview Survey; NSAF = National Survey of America’s Families; NSCH = National Survey of Children’s Health; SCHIP = State Children’s Health Insurance Program.
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Methodology
Findings
CSHCN eligible for SCHIP but uninsured compared to CSHCN enrolled in SCHIP; regression adjustment for demographic characteristics and income.
Uninsured children significantly more likely to have unmet health care needs (odds ratio = 5.92).
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TABLE D-5 Impacts of Health Insurance on Children’s Health Status and Related Outcomes
Citation
Place and Time Period of Analysis
Data Sources
Late Diagnosis
Froehlich et al. (2007)
Prevalence, recognition, and treatment of attention-deficit/hyper-activity disorder in a national sample of U.S. children
United States, 2001-2004
Children ages 8-15 in the NHANES who were screened for and identified with ADHD (N = 222)
Maniatis et al. (2005)
Increased incidence and severity of diabetic ketoacidosis among uninsured children with newly diagnosed type 1 diabetes mellitus
Barbara Davis Center for Childhood Diabetes, University of Colorado Health Sciences Center, 2002-2003
Medical record review for all children with Type 1 diabetes (N = 383)
Preventable Hospitalization
Aizer (2007)
Public health insurance, program take-up, and child health
California, 1996-2000
Zip code–level/race/ethnicity level quarterly data on: Medicaid enrollment, ACSC hospitalizations, and child population counts from Medicaid enrollment files, state hospital discharge files from California’s Office of Statewide Planning and Human Development, and U.S. census
Bermudez and Baker (2005)
The relationship between SCHIP enrollment and hospitalizations for ambulatory care sensitive conditions in California
California, 1996-2000
County-level monthly data on: SCHIP enrollment, ACSC hospitalizations, and child population counts from SCHIP enrollment files, state hospital discharge files from California’s Office of Statewide Planning and Human Development, and U.S. census
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Methodology
Findings
Uninsured children with ADHD compared to insured children with ADHD; regression adjustment for differences in demographic characteristics and income.
Uninsured children less likely to have previously received a diagnosis of ADHD at the time of the examination (odds ratio = .1).
Uninsured children compared to privately insured children; no regression adjustment differences in characteristics.
Uninsured children were significantly more likely to present with diabetic ketoacidosis (odds ratio = 6.19) and severed diabetic ketoacidosis (odds ratio = 6.09).
Two-stage instrumental variable regression analysis predicting first the rate of Medicaid enrollment using placement and timing of outreach investments (e.g., application assistors and advertising campaigns), and then the rate of ACSC admissions, controlling for zip code characteristics including income and county fixed effects. Uses alternative instruments and also explored possible effects on length of stay.
Higher Medicaid enrollment rate is associated with a lower ACSC admission rate. A 10 percent increase in Medicaid enrollment leads to a 2.3 to 3.4% decrease in Medicaid ACS hospitalizations. Similar range found under alternative specifications. The OLS estimates were smaller in absolute value.
A regression model predicted the rate of ACSC hospitalization per child ages 1-18, controlling for the rate of SCHIP enrollment in the county (lagged by 1 year), county-level demographics (including income), pediatric provider supply, and county fixed effects. As a control, test whether SCHIP enrollment affected ACSCs among adults ages 19 to 29 or admission for appendicitis, which is not an ACSC.
A 1 percentage point increase in SCHIP enrollment was associated with a reduction of .86 ACSC hospitalizations per 100,000 children, a significant but small effect compared to a mean of 28.9. There was no significant change for young adults. Appendicitis hospitalization rates also declined significantly, but at a much lower level.
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Citation
Place and Time Period of Analysis
Data Sources
Cousineau et al. (2008)
Preventable hospitalizations among children in California counties after child health insurance expansion initiatives
9 counties in California that implemented CHIs to cover uninsured children, 2000-2005
Quarterly hospital discharge data on ACSCs
Szilagyi et al. (2006)
Improved asthma care after enrollment in the state children’s health insurance program in New York
New York State, 2001-2002
Two-wave telephone survey of parents of children with asthma in Child Health Plus—SCHIP (N = 334 at baseline and 364 at followup)
Perceived Health Status/Missed School Days/Other
Currie et al. (2008)
Has public health insurance for older children reduced disparities in access to care and health outcomes?
United States, 1986 to 2005
NHIS (N = 548,789)
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Methodology
Findings
ACSC rates are modeled as a function of CHI implementation, time, county, and insurance. Changes in ACSC rates for children who are either publicly insured or self-pay in each of the nine CHIs are compared to changes occurring among other children.
The rate of hospitalization for ACSCs declines following CHI implementation for lower-income children, while there is no change for higher-income children.
Responses for parents of newly enrolled children compared to responses for the same parents 1 year later.
After 1 year enrolled in SCHIP, the percentage of children hospitalized for asthma in the past year declined significantly from 11.1 to 3.4%. There were also significant reductions in emergency room visits and other health care visits for asthma.
Examine impacts of Medicaid/SCHIP eligibility expansions on probability of a physician visit and reported health status using a simulated eligibility indicator to address potential endogeneity of eligibility. Medicaid/SCHIP generosity index generated by applying state eligibility rules to a sample of children for each state and year. Control variables include interaction terms and age and year dummies. Look at concurrent and lagged effects. Still potentially biased and concerns about appropriateness of simulated eligibility measure in studies of all kids. Service use refers to previous 12 months.
No statistically significant concurrent effects on perceived health status. Statistically significant, positive effects of eligibility for children ages 2, 3, and 4 on health status of children ages 9 to 17, suggesting that the effects of insurance coverage on perceived health do not show up immediately.
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Citation
Place and Time Period of Analysis
Data Sources
Damiano et al. (2003)
The impact of the Iowa S-SCHIP program on access, health status, and family environment
Iowa, 1999-2000
Two-wave mail survey (with telephone followup) of parents of new enrollees in Hawk-I (SCHIP) and 1 year later; (N = 463) response rate = 80% for baseline and 72% for followup
Fox et al. (2003)
Changes in reported health status and unmet need for children enrolling in the Kansas children’s health insurance program
Kansas, 1999-2000
Two-wave survey of parents of children enrolled in the program in its first six months and of the same parents 1 year later; N = 1,955, response rate = 60% (Wave 2)
Howell and Trenholm (2007)
The effect of new insurance coverage on the health status of low-income children in Santa Clara County
Santa Clara County, CA, 2003-2004
Survey of parents of undocumented children enrolled in Healthy Kids insurance; (N = 1,235) response rate = 89%
Howell et al. (2008a)
Final report of the evaluation of the San Mateo County Children’s Health Initiative
San Mateo County, CA, 2006-2007
One-wave survey of parents of primarily undocumented children newly enrolled in Healthy Kids insurance and enrolled for 1 year; (N = 1,404), response rate = 77%
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Methodology
Findings
Pre-post cohort/longitudinal design. Outcomes for new enrollees compared to outcomes for the same enrollees 1 year later; no information provided on prior coverage of new enrollees. Service use refers to previous 12 months.
The proportion of children identified as being in excellent or very good health by their parents increases significantly from 79% to 82%. The proportion of children who missed 5 or more days of school due to illness or injury declined significantly from 35% to 25%.
Pre-post cohort/longitudinal design. Responses for children just after enrollment compared to responses for same children 1 year later. Service use refers to previous 12 months.
The proportion of children identified as being in excellent or very good health by their parents increases significantly from 71.2% to 75.7%. The proportion of parents who reported that their child’s health is better now than it was a year ago also increased significantly from 11.6% to 20.0%.
Newly enrolled children compared to children enrolled for 1 year (established); regression adjustment for demographic characteristics, income, and medical and dental need.
Percent in fair/poor health reduced by 13.0 percentage points; significant change for both those who enroll and do not enroll for medical reasons; percent with more than 3 school days missed in month is reduced by 5.8 percentage points among those not enrolling for a medical reason.
Newly enrolled children compared to children enrolled for 1 year; regression adjustment for demographic characteristics, income, and medical and dental need. Service use refers to previous 6 months.
No significant effect on perceived health status. Significant reduction in percentage of children with missed school days in past 4 weeks, from 47.5% to 40.8%.
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Citation
Place and Time Period of Analysis
Data Sources
Howell et al. (2008b)
The impact of the Los Angeles Health Kids Program on access to care, use of services, and health status
Los Angeles County, CA, 2005-2007
Two-wave survey of parents of primarily undocumented children ages 1-5 enrolled in Healthy Kids insurance (N = 975); response rate = 86% (Wave 1) and 77% (Wave 2)
Szilagyi et al. (2004)
Improved access and quality of care after enrollment in the New York state children’s health insurance program
New York State, 2001-2002
Two-wave telephone survey of parents of children enrolled in Child Health Plus (SCHIP) for 4-6 months and about 1 year after enrollment; N = 2,290; response rate = 87% for followup
NOTE: Changes are statistically significant unless otherwise noted as “not significant” (“NS”). N/A indicates the study did not examine that outcome. ACSC = ambulatory care sensitive condition; CHI = children’s health initiatives; MEPS = Medical Expenditure Panel Survey; NHANES = National Health and Nutrition Examination Survey; NHIS = National Health Interview Survey; NSCH = National Survey of Children’s Health; OLS = ordinary least squares; SCHIP = State Children’s Health Insurance Program.
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Methodology
Findings
D-D; changes over a year for children who had been enrolled for a year in Wave 1 compared to changes for newly enrolled children; regression adjustment for demographic characteristics, income, and medical and dental need. Service use refers to previous 6 months.
D-D for percentage in excellent/very good health not significant; however both new and established enrollees improve significantly from Wave 1 to Wave 2.
Outcomes for newly enrolled children compared to outcomes for the same children 1 year later. Pre period includes insured and uninsured kids, but 80% uninsured for part of the year.
No significant effect on perceived health status.
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