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Data Needs for the State Children’s Health Insurance Program 3 Counting Enrollment The percentage of eligible children who are enrolled in SCHIP is an important measure of the success of the program in reducing the number of uninsured children. However, determining this percentage is problematic—both because the number of eligible children is difficult to estimate and because of the difficulty in estimating the number of SCHIP enrollees. This chapter discusses the estimates of the numbers of children enrolled in SCHIP and how they are obtained, reasons for nonenrollment of those who are eligible, and methods that have been employed to improve the rate of enrollment. ESTIMATING ENROLLMENT SCHIP enrollment can be determined either from administrative records or from sample surveys. Although administrative records may be seen as ideal for this estimation, in fact differences in the number of children “ever enrolled” versus the number enrolled at a point in time can lead to widely divergent enrollment estimates. The official federal estimate provided by the Centers for Medicare and Medicaid Services (CMS) estimates that nationally 3.3 million children were enrolled in SCHIP at some time during FY 2000, ending September 30, 2000 (U.S. Department of Health and Human Services, 2001). However, this number overstates the number of children enrolled at any point in time, due to the high rates of mobility in SCHIP eligibility and enrollment. Data obtained directly from the states
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Data Needs for the State Children’s Health Insurance Program by Kaiser Family Foundation show that only 2.3 million children were enrolled in June 2000 (Smith and Rousseau, 2001). Bilheimer reported on data from Oregon and Kansas that illustrate the high levels of volatility in insurance status for the SCHIP-eligible population. The Oregon data indicate that half of the SCHIP enrollees came directly from Medicaid and almost half of the SCHIP disenrollees went back to Medicaid. Kansas reported that three-quarters of their first-time SCHIP enrollees had been in Medicaid at some point prior to their enrollment in SCHIP and that more than one-third of their SCHIP disenrollees went directly into Medicaid. Bilheimer argued that because of the many transitions, the point-in-time number is much more meaningful than the ever-enrolled number. Administrative data may not provide a completely accurate picture of SCHIP enrollment due to inadequacies in some state’s administrative data systems. Lack of a consistent identifier for a child over time may make it difficult to distinguish whether the same child is enrolling and reenrolling, or whether two distinct children are enrolled. Creating identifiers that track all of the children in a family is also important. This was complicated, however, by the fact that, prior to June 25, 2001, states were prohibited from asking SCHIP enrollees for their Social Security numbers. Some states that have chosen to implement SCHIP by expanding Medicaid have incorporated the reports on their SCHIP enrollees into their preexisting Medicaid data systems. As Bilheimer pointed out, the latter were primarily designed to track enrollment and pay medical bills and are often ill suited for use as a management tool. Although SCHIP provides the opportunity to put in place data systems better suited for management purposes, these systems still need to interface with the Medicaid data systems, given the high rate of transition between the two programs. Given the difficulties in relating administrative data to an appropriate estimate of the number of eligible children, some sample surveys estimate both the number eligible for participation in SCHIP and the number enrolled. For example, Dubay reported that the National Survey of America’s Families oversamples low-income populations, thus permitting national estimates as well as more disaggregated estimates of enrollment in 13 states. Among the 13 states, the estimates of percentage of eligible children enrolled in Medicaid in 1999 ranged from 58.4 percent in Texas to 92.7 percent in Massachusetts. Enrollment in SCHIP ranged from a low of 34.7 percent of eligible children in Florida to 88.1 percent in Massachusetts.
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Data Needs for the State Children’s Health Insurance Program Surveys are also subject to error, including reporting error. Some respondents reply that they are enrolled in SCHIP when they are not, while others reply that they are not enrolled when they are. Gestur Davidson reported that a 1999 survey in Minnesota showed that a large number of those known to be on Medicaid responded that they were on SCHIP, whereas most of those known to be on SCHIP replied that they were covered by SCHIP. The resulting survey estimates of the number enrolled in SCHIP exceeded the numbers reported in Minnesota’s administrative data. David Hanig reported similar mismatches in the state of Washington, where the survey estimates of Medicaid enrollees greatly exceeded the number of Medicaid enrollees recorded in administrative data. This problem was most pronounced in counties with a large proportion of Hispanic migrant workers, suggesting either a problem with the time period covered or with respondents’ understanding of the survey question. REASONS FOR NONENROLLMENT OF ELIGIBLE CHILDREN While national surveys can be used to estimate numbers of enrollees, few of them pinpoint reasons that eligible children are not enrolled in SCHIP. State-specific surveys can be very helpful in determining if state policies (such as the length of the application or documentation requirements) are impeding enrollment and can also help identify geographic regions where enrollment efforts should be enhanced. Based on the results of state-specific surveys, the Michigan SCHIP instituted several changes in its application process that substantially decreased the number of incomplete applications. These changes included: reordering the questions on the application form and simplifying the language; reducing the documentation requirements, which had required, for example, a copy of the child’s Social Security card; allowing self-declaration of income rather than requiring that the applicant submit pay stubs; and discontinuing the practice of income verification except on a sample basis. Other states have made similar changes with positive results on enrollment rates. Given the sample sizes and confidentiality constraints in national surveys, state-specific surveys are also required to understand divergent enrollment trends in different areas of a state. Paul-Shaheen emphasized the importance of state surveys to identify where within the state to direct limited resources for increasing enrollment in the program. Norton reported that in New Hampshire a large state survey revealed that specific
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Data Needs for the State Children’s Health Insurance Program rural areas had considerably higher rates of uninsured children. These areas were then targeted for enhanced outreach efforts. METHODS TO IMPROVE ENROLLMENT RATES Children who are eligible for SCHIP may already be enrolled in a number of social programs targeted to low-income children. This overlap across programs makes it possible to target SCHIP to children who may not yet be enrolled but who have a high probability of being eligible. In her analysis of data from the 1999 National Survey of America’s Families, Genevieve Kenney found that almost three-quarters of the uninsured children participated in the National School Lunch Program, the Special Supplemental Nutritional Program for Women, Infants, and Children (WIC), or the Food Stamp Program. The survey revealed that about 45 percent of the parents of the uninsured children had heard of the SCHIP and Medicaid programs, but they did not know that they did not have to be on welfare to participate. Families that participate in federal food programs represent a significant target for outreach efforts for both Medicaid and SCHIP because of the overlap in eligibility and the fact that the application process for the food programs is much simpler than that for Medicaid or SCHIP. The state of Washington has successfully linked the medical insurance application system with the school lunch system to increase outreach for SCHIP. The SCHIP program made an arrangement with the schools to add a check box on the school lunch application form indicating whether the applicant wanted medical coverage. While this is a promising approach, it has some complications. Almost all of the participants in the school lunch program are eligible for Medicaid or SCHIP, and a large percentage are already participating in one of those programs. As a result, for those forms on which the box had been checked, it was necessary to check names against Medicaid and SCHIP enrollment records so that application forms would not be sent to those who were already in one of these programs. The initial results showed an enrollment yield of less than 5 percent. New Jersey also developed a program to coordinate applications for SCHIP with the state’s school lunch program. Heidi Smith reported that since the school lunch application was a Department of Education form, getting a health insurance question on the form had to be coordinated with that department. The New Jersey Family Care agency wrote a letter, signed by the Commissioner of Education, to the school superintendents about
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Data Needs for the State Children’s Health Insurance Program the health insurance program asking the schools to cooperate. Family Care then sent a letter to the school principals asking them to send copies of all the forms that had a check mark in the health insurance box to Family Care for potential enrollment. The response was initially problematic, because many of the principals did not forward copies of the forms. The help of the school nurses was enlisted, and they were successful in seeing that most of the forms were forwarded to the Family Care agency. The number enrolled through this process was relatively low, but improvements were instituted for the following year with the expectation of better results. The overlap between Medicaid and SCHIP eligibility must also be considered when seeking ways to enhance SCHIP enrollment. Dubay concludes that reducing the uninsurance rate among low-income children must involve targeting Medicaid-eligible children, as well as those eligible for SCHIP, because 60 percent of uninsured children are eligible for Medicaid, while only 25 percent are eligible for SCHIP. State-specific surveys identified cumbersome application procedures as an impediment to enrollment for many SCHIP-eligible children. Michigan found that many of those who requested application forms did not return them because the forms were too confusing. This was remedied by a substantial revision of the form. A promising strategy that some states are using to increase enrollment in SCHIP is presumptive eligibility without requiring documentation of income or assets. To control the proportion of those who are actually ineligible from enrolling, some states audit the incomes of a sample of enrollees and make it known to enrollees in advance that they may be included in the audit sample. This policy is used as a possible deterrent to misrepresentation. Evidence from some of the states seems to indicate that a vast majority of the enrollees sampled have met the eligibility criteria. Michigan, for example, found that 94 percent entered their incomes correctly and that some of those who did not had reported income that was too low for SCHIP but not too low for Medicaid. An alternative method of checking on error rates is to “plant” persons of known eligibility status into the applicant pool and to determine whether they are approved for enrollment or not. Based on the workshop discussion the panel concluded that enrollment could be improved by a number of means: Continuing to share state experiences to identify the most effective ways to get hard-to-enroll eligible children enrolled with mini
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Data Needs for the State Children’s Health Insurance Program mum error rate. As budgets tighten, cost effectiveness becomes even more important. Implementing presumptive eligibility on the basis of self-reporting of income, with income auditing, using sample-based auditing as a way to measure and limit error rates in enrollment. Continuing to apply lessons learned in SCHIP outreach to improve Medicaid outreach. States should consider using the school lunch program and the Special Supplemental Nutrition Program for Women, Infants, and Children to target SCHIP-eligible children.
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