Lack of health insurance coverage is a significant barrier to accessing needed health care and to maintaining financial security.
The Kaiser Family Foundation released a report in December 2017 that outlines the effects insurance has on access to health care and financial independence. One key finding was that “Going without coverage can have serious health consequences for the uninsured because they receive less preventative care, and delayed care often results in serious illness or other health problems. Being uninsured can also have serious financial consequences, with many unable to pay their medical bills, resulting in medical debt.”
Uninsured Children is a Percentage
Uninsured Children is the percentage of the population under age 19 that has no health insurance coverage in a given county.
Uninsured Children is Created Using Statistical Modeling
Uninsured Children is created using complex statistical modeling. Modeling generates more stable estimates for places with small numbers of residents or survey responses. There are also drawbacks to using modeled data. The smaller the population or sample size of a county, the more the estimates are derived from the model itself and the less they are based on survey responses. Models make statistical assumptions about relationships that may not hold in all cases. Finally, there is no perfect model and each model generally has limitations specific to their methods.
The numerator is the number of people under age 19 who currently have no health insurance coverage. A person is uninsured if they are not currently covered by insurance through a current/former employer or union, purchased from an insurance company, Medicare, Medicaid, Medical Assistance, any kind of government-assistance plan for those with low incomes or disability, TRICARE or other military health care, Indian Health Services, VA, or any other health insurance or health coverage plan.
The denominator is the county population under age 19.
This measure can be used to track progress with come caveats. Modeled estimates have specific drawbacks with regard to their usefulness in tracking progress in communities. Modeled data are not particularly good at incorporating the effects of local conditions, such as health promotion policies or unique population characteristics, into their estimates. Counties trying to measure the effects of programs and policies on the data should use great caution when using modeled estimates. In order to better understand and validate modeled estimates, confirming this data with additional sources of data at the local level is particularly valuable.
Years of Data Used
Small Area Health Insurance Estimates
The US Census Bureau's Small Area Health Insurance Estimates (SAHIE) program produces estimates of health insurance coverage for all states and counties. In July 2005, SAHIE released the first nationwide set of county-level estimates on the number of people without health insurance coverage for all ages and those under 18 years old. SAHIE releases estimates of health insurance coverage by age, sex, race, Hispanic origin, and income categories at the state level and by age, sex, and income categories at the county level.
 Kaiser Family Foundation. The Uninsured: A Primer - Key Facts about Health Insurance and the Uninsured Under the Affordable Care Act. December, 2017.