States have three options for designing their CHIP programs: Medicaid expansion CHIP, separate CHIP, and combination CHIP. Medicaid expansion CHIP. States may operate CHIP as an extension of their Medicaid programs. Under Medicaid expansion CHIP, states expand income eligibility levels for children beyond those of the state’s Medicaid program. Medicaid expansion CHIP programs must follow Medicaid rules, including providing all Medicaid covered benefits to enrolled children. Separate CHIP. States may operate their CHIP programs separate from their Medicaid programs. In so doing, the states are not required to follow the same rules as Medicaid; thus, these states have some additional flexibility in designing CHIP, such as determining which benefits to offer and how, if at all, to charge premiums. Combination CHIP. States may have a combination program, where they operate a separate CHIP program, as well as a Medicaid expansion CHIP program, each for a different population of children. For example, some states that operate combination CHIP programs apply different age or income eligibility requirements for their Medicaid expansion CHIP and separate CHIP programs. Similar to Medicaid, CHIP program expenditures are shared between the states and the federal government, but federal matching rates for CHIP are higher than for Medicaid and federal funding for CHIP is capped, with states receiving annual CHIP allotments. The type of CHIP program a state designs may affect the amount of federal funding available to that state in the event the state exhausts available CHIP funding for the year. A state with a Medicaid expansion CHIP program that exhausts available CHIP funding may apply Medicaid funds at the Medicaid matching rate to remaining expenses for enrolled children for that year. However, a state with a separate CHIP program that exhausts available funding would not have access to such funding. In general, states administer CHIP under broad federal requirements that permit flexibility in how they design their programs, including in the services they cover, their upper income eligibility limits, and the fees they charge to participate. In terms of income eligibility, as of January 2019, 19 states, including the District of Columbia, had CHIP upper income eligibility limits of 300 percent of the FPL or higher compared with 32 states whose CHIP upper income eligibility limits were below 300 percent of the FPL. (See fig. 1.) In addition, states can charge beneficiaries fees for CHIP coverage. These fees can vary depending on whether they are enrollment fees, premiums, or other types of cost sharing. Among the states that charge CHIP premiums, the premiums can vary based on family income and the number of children in CHIP. (See table 1.) Although states may charge premiums or have other cost sharing, according to CMS, CHIP provides more affordable coverage than is generally available in the private health insurance market. CHIP crowd-out may occur when employers modify or decide not to offer health insurance to their employees or to their dependents, because of CHIP availability. For example, employers who are aware of CHIP may decide not to offer health insurance to employees or their dependents due to concerns about the costs of providing insurance, especially for smaller sized firms, or as a result of changes in federal or state policies, such as requirements resulting from PPACA. Crowd-out may also occur when employees drop or decide not to enroll in insurance offered by their employers and enroll their children in CHIP, because of CHIP availability. As we have identified in prior work, assessments of the potential for crowd-out must take into account an understanding of the extent to which private health insurance is available and affordable to low-income families who qualify for CHIP. National survey results show that private health insurance is the most prevalent source of insurance for children; however, there is substantial variation across states in coverage rates. Additionally, the extent to which employers offered individuals insurance varies by family income. For additional information on factors that may affect crowd-out, see appendix I. For information on sources of health insurance for children under age 19, including CHIP and employer sponsored insurance, see appendix II. The type of CHIP program a state designs affects its responsibilities for monitoring and mitigating the potential for CHIP crowd-out. The 42 states with separate CHIP programs—including those in combination CHIP states—are required to submit CHIP plans that describe reasonable procedures to prevent crowd-out and to report annually to CMS on certain crowd-out related indicators, such as the number of CHIP applicants with access to private health insurance; however, CMS provides states flexibility to decide which crowd-out prevention procedures to use. For example, states can require CHIP applicants to undergo a period of uninsurance prior to enrollment, known as a waiting period, to deter families that have access to private health insurance from dropping that insurance to enroll in CHIP. In contrast, states are not required to take steps to prevent crowd-out for their Medicaid expansion CHIP programs and may only do so if consistent with the Medicaid statute, or if under an approved section 1115 demonstration, which allows states to implement policies that waive certain Medicaid requirements. For states with separate and combination CHIP programs, CMS provides general guidance for minimizing crowd-out, which the agency has modified over time. (See table 2 for a description of the crowd-out related responsibilities.) For example, in 2013, CMS issued regulations to align with a PPACA provision for health plans and health insurance issuers that limited waiting periods to a maximum of 90 days, and established mandatory waiting period exemptions. The regulations also eliminated the application of a CHIP policy requiring that states with separate CHIP programs have different crowd-out prevention procedures in place for children at different income levels. In making this change, CMS noted that available research called into question the prevalence of crowd-out. CMS indicated that its policy still required states to monitor crowd-out and, if a high rate of crowd-out were to occur, states should consider implementing prevention procedures, such as public outreach about other health care options available in the state. In response to crowd-out related recommendations we made in 2009, CMS modified its guidance to collect additional information from states in their 2009 through 2013 annual reports on how they assess the availability and affordability of private health insurance for CHIP applicants. For example, from 2009 through 2013, states were required to report to CMS if the state’s CHIP application asked if applicants had access to private health insurance. Additionally, states that operated a waiting period without affordability exceptions were asked if the state collected data on the cost of health insurance for an individual or family. However, CMS officials stated that the agency eliminated the questions regarding affordability of private health insurance in 2013, as part of efforts to update the electronic system states use to submit their CHIP annual reports to reflect PPACA enrollment simplification and coordination requirements. CMS officials said some of the questions were duplicative of other state reporting requirements and other questions were deemed irrelevant in light of the establishment of affordability exceptions to waiting periods. States reported indicators of potential crowd-out to CMS in their annual reports, although some do not report on these indicators and those that do may calculate them differently. The states also varied in the extent to which they have processes for directly estimating crowd-out; however, CMS officials and officials in selected states told us they understand the occurrence of crowd-out to be low. Further, we identified few published research studies that directly estimated crowd-out; each used different methodologies, resulting in varied estimates. States with separate CHIP programs—including those in combination states—are required to annually report indicators of potential crowd-out; states must also describe in their CHIP plans other indicators of potential crowd-out they collect. CMS’s 2017 CHIP annual report asks these states to report on crowd-out related questions, including two indicators of crowd-out: (1) the percentage of individuals who enrolled in CHIP that have access to private health insurance, and (2) the percentage of CHIP applicants who cannot be enrolled, because they have private health insurance—an indicator of potential crowd-out averted. However, not all states with separate CHIP programs track and report information related to these two indicators of potential crowd-out, and those that do may calculate these indicators differently. For example, of the 42 states with separate CHIP programs, the 2017 annual reports showed the following: Four of the 42 states reported that they tracked the number of individuals who have access to private health insurance; the remaining 38 states either did not report tracking this information or did not respond to this question. Of the four states tracking this information, the percentages reported ranged between 0.5 percent and 7 percent of CHIP applicants who have access to private health insurance. Twenty-one of the 42 states reported that they tracked the percentage of applicants who could not be enrolled in CHIP because they were enrolled in private health insurance; the remaining 21 states did not report this percentage to CMS. This is a measure of crowd-out averted due to state oversight of its enrollment process. The percentages reported by the 21 states tracking this information ranged from 0 percent in several states to 18 percent in one state. Among the states that reported they do not track individuals with access to private insurance and did not provide a percentage of applicants not enrolled in CHIP because of enrollment in private health insurance, five states indicated that either their electronic eligibility systems did not allow them to capture this information or the data to report this information were not available. CMS officials acknowledged that not all states report on these indicators; however, they noted that states operating separate CHIPs have other processes in place to prevent children with other health insurance from enrolling in CHIP. Further, some states that operate separate CHIP programs describe approaches for directly estimating crowd-out in their CHIP plan amendments. The results of these estimates are not reported to CMS unless they reach a threshold defined by each state. In 2013, CMS required separate CHIP states to submit state plan amendments to CMS to update their eligibility-related policies, including their crowd-out prevention procedures. In response, 17 of the 42 states submitted these amendments and described approaches they would use to directly measure crowd-out. For example: Colorado reported conducting a biennial survey to estimate the percentage of enrollees who dropped group health insurance without good cause to gain eligibility for CHIP, according to its CHIP plan. Connecticut reported comparing the number of children denied CHIP enrollment because they were enrolled in private health insurance to those same applicants who reapplied for CHIP 6 months later, but did not have private health insurance. The crowd-out threshold defined by Colorado and Connecticut is 10 percent; therefore, if these states’ crowd-out estimates were to exceed 10 percent, each state would collaborate with CMS to identify other procedures to reduce crowd-out. According to CMS officials, no state using this approach to estimate crowd-out has exceeded the percentages established or expressed concerns with crowd-out. States we interviewed varied in the extent to which they estimate crowd- out; however, most states did not view crowd-out to be of concern. Among our six selected states with separate CHIP programs, one state— New York—directly measures crowd-out. New York asks applicants that dropped their private insurance in the last three months the reasons why they dropped this coverage, which includes responses such as the family’s preference for the child to have CHIP benefits over their previously held private health insurance. New York state officials told us they consider instances of crowd-out to include when individuals drop private insurance because CHIP costs and benefits are more favorable. For the last 9 months of 2014, the officials estimated crowd-out in New York to be about 1.9 percent. If New York estimates crowd-out to be higher than 8 percent, state officials told us they will report this to CMS and work with CMS on implementing additional crowd-out prevention procedures. Officials from the other five selected states said they do not actively measure crowd-out, some of them citing limited resources and difficulties developing estimates, and noted that crowd-out was not a high priority for them, because they did not think crowd-out was prevalent in their states. For example, officials from two states said they had not heard any concerns regarding crowd-out from their state legislature, state insurance agencies, or others. CMS officials also told us that no state had reported concerns about crowd-out. Our review identified few research studies that directly estimated CHIP crowd-out. Specifically, we identified three research studies published from 2013 to 2018; each used different methods and arrived at varying estimates of crowd out. One study estimated crowd-out across 15 states that expanded their CHIP income eligibility requirements between 2008 and 2012 by examining health insurance enrollment changes in a sample of children after they became newly eligible for CHIP. This study estimated that public insurance among children under age 19 increased about 2.9 percentage points during this period, and private insurance decreased by 1.8 percentage points. The study reported that 63 percent of the 2.9 percentage point increase in public insurance was due to crowd-out. The researchers also produced state-level estimates for the effects of CHIP income eligibility expansions on insurance coverage in newly eligible children. These estimates varied by state, suggesting that crowd-out also varies by state. In particular, three states had an increase in public insurance ranging from about 4 to 12 percentage points, and three states had a decrease in private insurance that ranged from about 7 to 14 percentage points. The researchers noted they did not account for factors that may have caused privately insured individuals to increase their use of public insurance, such as changes in the affordability of private health insurance. Another study estimated the effect of CHIP income eligibility expansions on crowd-out in Illinois. This study examined the differences in public and private health insurance between children in Illinois, where CHIP income eligibility was expanded, and children from a combination of other states that did not expand CHIP—and were chosen to resemble the demographic characteristics and health insurance profile of Illinois. This study found a 6.5 percentage point increase in CHIP enrollment in 2010 among families between 200 percent and 300 percent of the FPL, and estimated that 35 percent of this increase in CHIP enrollment was due to crowd-out. At other income levels higher than 300 percent of the FPL, the study found either no net effect on private health insurance, or an increase. The third study estimated public and private insurance under different CHIP income eligibility thresholds and different premium schedules. While the study estimated that a CHIP expansion from 200 to 400 percent of the FPL with no premium contribution and a 4 month waiting period increased CHIP enrollment by about 4.5 percentage points and decreased private coverage by about 2.2 percentage points, these estimates do not provide evidence of crowd-out, because the differences in these percentage point estimates were not statistically significant. Although not reporting direct estimates of CHIP crowd-out, we identified other studies that provide related information. For example: In one study, researchers surveyed the parents of current and former CHIP enrollees in 10 states to examine access to private coverage for children enrolled in CHIP. This study found that about 13 percent of new CHIP enrollees had private health insurance in the year before enrolling in CHIP. Among the 13 percent, about 18 percent reported that they dropped their private health insurance, because CHIP was more affordable, and about 5 percent dropped their private health insurance, due to a preference for CHIP. The authors noted that access to private coverage among CHIP enrollees is low and when access is available, affordability is a serious concern for parents. The authors concluded that this suggests limited potential for crowd-out. A study published in 2015 that surveyed the parents of about 4,100 new CHIP enrollees to understand why children enrolled in CHIP, among other things, found that 35 percent of these parents reported applying for CHIP, because it was more affordable than the other health insurance options they could obtain for their children. Representatives from national organizations, researchers, and CMS officials we interviewed noted some of the challenges measuring the extent of CHIP crowd-out, including the limitations of available data sources; however, they did not consider crowd-out to be prevalent. For example: Some data sources do not separately collect or categorize CHIP information. For example, the ACS does not specifically ask respondents if their children have health insurance through CHIP; thus, researchers have to manipulate the data to separate CHIP coverage from other forms of public health insurance, such as Medicaid. The methodologies available to separate CHIP from Medicaid respondents have many limitations, according to researchers and U.S. Census Bureau officials we contacted. Accurate crowd-out estimates require researchers to account for the reasons why someone dropped his or her health insurance and enrolled in CHIP, and this information is not captured by national surveys. Researchers may also vary in what they consider to be crowd-out; for example, some may not consider dropping private health insurance and enrolling a child in CHIP because of a job loss or change in employment to constitute crowd-out. Others do not consider it to be CHIP crowd-out when parents drop their private health insurance and enroll in CHIP, because CHIP is more affordable. CMS officials also noted complexities in measuring crowd-out—such as variation in definitions of crowd-out and methodologies for measuring it—and they said that the agency has not conducted or commissioned its own evaluation. However, CMS officials reiterated that no state has reported concerns with crowd-out and based on their review of studies conducted by researchers understand that its prevalence is likely low. CMS monitors states’ CHIP crowd-out prevention procedures and offers technical assistance, while states ask CHIP applicants about other sources of health care coverage, and use waiting periods and cost- sharing procedures, such as enrollment fees and premiums. Several state officials we interviewed told us that their crowd-out prevention procedures are effective; however, they could not speak to the effectiveness of any particular procedure and few studies have examined the issue. CMS officials told us that they track the information states submit about their CHIP crowd-out prevention procedures as part of their annual report review process to identify any inconsistencies between the information contained in their state plans and the information submitted in states’ annual reports, among other reasons. When CMS officials identify any noticeable differences in the information reported by states from year-to- year in the annual reports—such as the percentage of CHIP applicants with access to private insurance—they told us they follow-up with the state to obtain additional information about these differences, and, if needed, advise states on ways they can prevent crowd-out. CMS officials also told us they provide technical assistance, when requested, to assist states in developing crowd-out prevention procedures. For example, CMS officials said they provided states with technical assistance after issuing regulations in 2013 on the use of waiting periods that also required states to update their state plan amendments. CMS officials said they have no plans to develop additional strategies for collecting states’ crowd-out information, because states have not reported crowd-out to be a concern, and there is no need to re-examine states’ oversight if prevalence as measured in research is likely low. All 42 states with separate CHIP programs reported to CMS that they had implemented at least one of the following six types of procedures to prevent crowd-out: (1) asking about other health insurance and denying CHIP coverage if other sources of health insurance are identified; (2) implementing cost sharing for CHIP coverage; (3) conducting database checks for other health insurance; (4) implementing a waiting period for CHIP coverage; (5) measuring crowd-out and taking steps if certain thresholds are exceeded; and (6) offering premium assistance for private health insurance. The majority of these states (36 of the 42 states with separate CHIP programs) implemented at least three crowd-out procedures. All 42 states with separate CHIP programs asked applicants about other insurance coverage on their CHIP applications to deny applicants CHIP coverage if private insurance coverage was found, and CMS officials told us that 35 of those states required CHIP enrollees to pay premiums or make other financial contributions to the cost of the coverage. (See table 3.) Among our six selected states with separate CHIP programs, there were differences in how some crowd-out procedures were implemented. For example, three states conducted database checks to see if applicants had other sources of health insurance; however, one state checked prior to enrollment, another checked at enrollment and during application renewal, and one state ran weekly checks. Among our six selected states with separate CHIP programs, none planned to change procedures to prevent potential crowd-out. Among the 42 states with separate CHIP programs, some crowd-out prevention procedures vary or have changed over time. For example, while many states use a private company to collect state and national health insurance coverage information to conduct database checks, another state developed a database that contains information on insurance coverage available through over 40,000 employers in the state. Additionally, prior to 2014, 36 states imposed waiting periods, during which applicants could not have health insurance for a specified time before CHIP enrollment, to prevent crowd-out. In 2017, 14 states used waiting periods. Prior to PPACA and the implementation of CMS regulations that limited waiting periods to 90 days, waiting periods could range from 1 to 12 months. After CMS updated its regulation, 21 states eliminated their waiting periods and five states shortened them. Among our four selected states with separate CHIP programs that shortened or eliminated their waiting periods, none of the state officials expressed concerns that this change contributed to CHIP crowd-out. Administering a waiting period may involve the state tracking or determining whether the applicant meets any of the state and federal waiting period exemptions, the number of months for the waiting period before the applicant can be enrolled in CHIP, and informing the federally facilitated exchange if an exemption to the waiting period applies to the applicant. As a result, some officials noted that reducing waiting periods eased their state’s administrative burdens, as well as eliminated gaps in children’s health insurance. Among the four selected states, officials from New York said they eliminated their waiting periods because, after undergoing the various administrative steps to verify each application and apply the waiting period, the majority of the CHIP applicants met at least one waiting period exemption. However, three of the selected states with separate CHIP programs maintained waiting periods, and state officials from Texas told us that few individuals met the waiting period exemptions. Some state officials told us they attributed waiting periods—which require children to go uninsured for a period of time—to gaps in health care, and their states eliminated the waiting period in an attempt to provide continuity in children’s access to health care. Although not required by law, officials from two of our selected states with Medicaid expansion CHIP programs told us their states previously had approved 1115 demonstration waivers permitting their states to use a CHIP waiting period, but eliminated them in 2013 and 2014 to close gaps in children’s health insurance coverage. Currently, these states use similar procedures as separate CHIP states to prevent crowd-out, according to state officials. Of our three selected states with Medicaid expansion CHIP programs, one state monitors CHIP enrollment trends; a second state requires its managed care organizations to check CHIP enrollees for other sources of insurance as part of their claim processing activities; and one state conducts database checks for other health insurance at the time of enrollment and re-enrollment. The effect of some of the states’ procedures on preventing CHIP crowd- out is unclear and, according to selected state officials and stakeholders, some crowd-out prevention procedures may have unintended consequences. For example, state officials and stakeholders told us waiting periods result in coverage gaps, which, as one stakeholder noted, could be catastrophic for a family with a sick child who would not have coverage during the waiting period. Several CHIP officials we interviewed believed their procedures are effective in preventing crowd- out; however, they either had not studied the effectiveness of their procedures or could not speak to the effectiveness of any particular procedure. Relatively few of the studies we reviewed examined the effectiveness of state procedures for preventing crowd-out. Specifically, two studies looked at this issue. Both studies concluded that cost-sharing procedures, such as premiums, can reduce the potential for crowd-out among higher- income CHIP-eligible families. A 2014 study used CHIP-related data from 2003 and found that CHIP premiums discourage individuals with private health insurance from dropping their insurance to enroll in CHIP. The study compared health insurance outcomes across 19 states for children with incomes slightly above states’ CHIP income eligibility thresholds with children in families with incomes slightly below the thresholds. The results indicated that there is an association between CHIP premiums and private insurance coverage; that is, a $1 increase in the CHIP premium above the income cut-off is associated with a 2.2 percentage point higher probability of the child being privately insured for families within 15 percent of the upper income level, and a 1.7 percentage point higher probability for families within 25 percent of the upper income level. These findings suggest that private health insurance may be a preferable alternative for CHIP eligible families at higher income levels who face higher CHIP premiums. A 2013 study used survey data from 50 states and the District of Columbia from 2002 to 2009 to estimate the effect CHIP premium contributions have on enrollment in CHIP, private insurance, and rates of uninsurance among children in families with income eligibility levels of 200 to 400 percent of the FPL. The study found that if CHIP programs expand eligibility to those at higher income levels and charge those families a higher premium, the families may be more likely to choose private health insurance, nullifying the effects of CHIP expansion among higher income families. We provided a draft of this report to HHS for review and comment. The department provided technical comments, which we incorporated as appropriate. As agreed with your offices, unless you publicly announce the contents of this report earlier, we plan no further distribution until 30 days from the report date. At that time, we will send copies to the Secretary of Health and Human Services, the Administrator of CMS, appropriate congressional committees, and other interested parties. In addition, the report will be available at no charge on the GAO website at http://www.gao.gov. If you or your staff members have any questions about this report, please contact me at (202) 512-7114 or at yocomc@gao.gov. Contact points for our Offices of Congressional Relations and Public Affairs may be found on the last page of this report. GAO staff that made key contributions to this report are listed in appendix III. Crowd-out may occur when employers modify or decide not to offer health insurance to their employees or to their dependents because of Children’s Health Insurance Program (CHIP) availability. For example, employers who are aware of CHIP may decide not to offer health insurance to employees due to concerns about the costs of providing insurance, especially for smaller sized firms, or as a result of changes in federal or state policies, such as requirements resulting from the Patient Protection and Affordable Care Act (PPACA). For example, PPACA required employers with a certain number of employees to offer their full-time employees a health insurance option meeting certain criteria, including affordability, or face tax penalties. Some researchers and policymakers expressed concern that this requirement may encourage employers to change how they offer insurance to employees, such as no longer offering family and dependent coverage, instead only offering health insurance to the employees, thereby causing employees with children to seek public insurance or insurance through health insurance exchanges. Other researchers and organizations point to PPACA increasing the availability of private health insurance offered by employers and through health insurance exchanges, particularly in areas and among populations where employer sponsored health insurance may not be as readily available. Crowd-out may also occur when employees drop or decide not to enroll in insurance offered by their employers and enroll their children in CHIP because of CHIP availability; however, as we have reported in the past, assessments of crowd-out should consider the affordability and availability of the employer sponsored insurance. For example, families with access to employer sponsored insurance may find CHIP more affordable or find CHIP benefits more comprehensive than employer sponsored insurance. Alternatively, they may find that CHIP provides better access to services specific to their child’s health care needs. For example, an evaluation of CHIP published in 2014 found that CHIP enrollees had better access to dental benefits than children with private insurance, although they were less likely to have a regular source of medical care and nighttime or weekend access to a provider. As we have identified in prior work, assessments of the potential for crowd-out must take into account an understanding of the extent to which private health insurance is available and affordable to low-income families who qualify for CHIP. American Community Survey (ACS) data showed that for 2013 through 2017, the most prevalent source of insurance for children in the United States under the age of 19 was private health insurance available through a parent’s employer or union. (See fig. 2.) Although private health insurance is the most prevalent source of insurance for children, there is substantial variation across states in coverage rates. (See fig. 3.) For example, in eight states, fewer than 40 percent of children were insured through an employer in 2017. In contrast, in Utah, more than 60 percent of families with children were insured by an employer in 2017. Medical Expenditure Panel Survey (MEPS) data show that the extent to which employers offered individuals insurance in 2013 through 2015 varied by family income. For example, MEPS Household Component data—which includes information on whether individuals were offered insurance by their employers—show that over 90 percent of families with incomes greater than 400 percent of the federal poverty level (FPL) were offered insurance by their employers from 2013 through 2015. The percentage of families offered insurance by their employers ranged from about 35 percent for families with incomes less than or equal to 138 percent of the FPL to about 85 percent for families with incomes above 300 and less than 400 percent of the FPL. (See fig. 4.) An Agency for Healthcare Research Quality (AHRQ) analysis of MEPS Insurance Component data—which includes information on whether employers offered insurance to their employees and the cost of that insurance— shows that in 2017, 24.2 percent of small employers (less than 50 employees) with a predominately lower-wage workforce offered their employees health insurance compared with 57.6 percent for small employers with a higher-wage workforce. In contrast, in 2017, offer rates at larger employers—that is, employers with more than 50 employees— was 94 percent for those with predominately lower-wage employees and 98.7 percent for large employers with predominately higher wage employees. With regard to affordability, the MEPS Insurance Component data show that average employee premium contributions for family coverage from 2013 through 2017 increased. Over this period, employees who work for employers with a predominantly lower-wage workforce—that is, employers that paid 50 percent or more of their workforce $12 or less per hour—contributed a larger amount and percentage of premiums to their employer-sponsored insurance than did employees who work for non- low-wage employers. (See fig. 5.) MEPS Insurance Component data also show that employees who work at establishments with a predominately lower-wage workforce enroll in insurance offered by their employers at a lower rate than employees of other establishments, though it is not known if this is due to affordability reasons. Finally, MEPS Insurance Component data show that the percentage of employees with deductibles and the amount of the deductibles have increased from 2004 to 2017. Between 2013 and 2017, average family deductibles increased about 36 percent, from $2,491 in 2013 to $3,396 in 2017. In addition, research published in 2018 on high deductible health insurance plans showed both increasing enrollment in these plans and that larger employers (1,000 or more employees) contributed more toward health insurance premiums for these plans than smaller employers (less than 25 employees). For example, according to this study: From 2006 to 2016, there was a 35 percentage point increase (11.4 percent to 46.5 percent) in enrollees in high-deductible health plans, with enrollees from smaller employers more likely to be enrolled in these plans compared with enrollees from larger employers (56.4 percent of enrollees from small firms compared with 42 percent of enrollees from large firms). A lower percentage of enrollees from the smaller firms had a plan with an employer-funded account, which defray health care costs, compared with enrollees from larger firms. For example, in 2016, only about one-third of enrollees in high-deductible health insurance plans from the smallest employers had an employer funded account to help pay for medical expenses compared with 89.3 percent of enrollees from the largest employers. High-deductible health insurance plan enrollees of the smallest employers were also more likely to not have the choice of an alternative plan type compared with enrollees from the largest employers. Although private health insurance is the most prevalent source of insurance for children, there is substantial variation across states in coverage rates. Figure 6 provides information on the percentage of children under age 19 insured through employer sponsored insurance, Medicaid, and the Children’s Health Insurance Program, as well as those who were uninsured in 2017. Carolyn L. Yocom, (202) 512-7114 or yocomc@gao.gov. In addition to the contact named above, individuals making key contributions to this report include Shannon Legeer (Assistant Director), Toni Harrison (Analyst-in-Charge), Mollie Lemon, and Courtney Liesener. Also contributing were Alison Binkowski, George Bogart, Jill Center, Leia Dickerson, Giselle Hicks, Drew Long, Kristeen McLain, Yesook Merrill, Jasleen Modi, Vikki Porter, Lisa Rogers, and Merrile Sing.