As a second predominant type of administrative data, vital statistics systems also can be linked to welfare data sets to provide a range of child health data. Issues of interest in using birth and death certificate files are described as follows:
- Although obtaining access to birth records varies in difficulty depending on many state characteristics, birth records carry information of at least three kinds: the timing and nature of the birth (e.g., family size, birth spacing); services and the payment source for the birth (e.g., prenatal care used and whether the birth was covered by private pay, Medicaid, or medically indigent funds); the family (e.g., marital status); and the well-being of the child at the time of birth (e.g., birthweight, length of hospital stay, 5- and 10-minute scores, and the presence of congenital abnormalities).
- Birth and death records increasingly are being maintained in electronic form, with greatly improved systems for updating this information in a more timely manner and linking these data for research purposes.
- Child death is another indicator that can show differences as a result of services received (Barth and Blackwell, 1998). Although preventing child death is not the primary or sole responsibility of public assistance programs alone, child death rates are sensitive to conditions affected by public assistance, including poverty and lack of supervision. For example, if TANF programs increase the likelihood of home visits by caseworkers who also look for dangerous conditions in the home, if they result in changes in parental substance abuse, if they change access to health care, if they lead to longer spells in which a child is not supervised, changes in death rates from accidents, illnesses, and overdoses could result. Thus, death rates and types of deaths that comprise that rate can change for program users, nonusers, and former users.
- A variety of relevant outcomes can be captured using death records, including adolescent suicide, adolescent homicide, many kinds of accidental deaths, deaths caused by injuries, deaths from abuse and neglect, and deaths caused by substance abuse (if overdose is the cause of death).
- Death records are in the public domain and are available at the state level as well as from the National Death Index (NDI)--a central computerized index of death record information on file in state vital statistics offices. Investigators also can obtain data at the state level and make arrangements with the appropriate state offices to obtain copies of death certificates or specific statistical information such as cause of death.
- Several public welfare agencies have matched child deaths against their welfare caseloads to better understand the vulnerability of their populations. Children who participate in AFDC, Medicaid, or Food Stamp Programs may experience an overall death rate greater than or different than that for other children (Maine Department of Human Services, 1983). Parents on welfare in Maine did not have mortality that was significantly higher than other children in poverty, although some types of mortality were high among welfare recipients; for example, the risk ratio for children whose parents were on welfare had a five times greater risk of experiencing a death from nonmotor vehicle accidents than other children in poverty. In a more recent study (Philips et al., 1999), mortality related to homicide, suicide, and automobile accidents (when substance abuse was mentioned on the death certificates) was shown to be substantially higher in the first week of the month--probably related to the greater availability of discretionary income following the arrival of government assistance checks and pay checks.
- Evaluations of the relationship between deaths and welfare changes need to assess the type and timing of the deaths. Because child mortality is relatively rare--even among high-risk populations--studies of welfare populations may need to combine these mortality data with injury data and incarceration data (discussed later in this paper) to obtain an overall assessment of significant threats to well-being.
Other data sets may not be as easily linked to welfare data sets, yet they should be considered. Twenty-one states have comprehensive databases on hospital discharges (Pappas, 1998). These data can provide information about a wide variety of health concerns, such as child injuries, acute illnesses, and emergency room visits. These data sets may include measures of income, payment authorization, or actual welfare status. Injury data can be linked to welfare participation for individual-level analyses if they can be obtained from local hospital organizations.
Data from school-based health centers are available in fewer places, but could be expected to become more useful as school-based health clinics expand their reach. Although not yet widely available, school-based health centers are growing in coverage and in some states now blanket the state. Some states, such as Massachusetts, have initiated statewide systems of maintaining school health data. School-based clinics often are under the umbrella of a local hospital, and can serve as Medicaid providers under managed care contracts. These data will be most useful when they cover a large proportion of all youth in the area under study and when they provide additional information not available in the Medicaid data. This is the case in Colorado and Connecticut, which have extensive school-based health center networks (Koppelman and Lear, 1998).
Another source of data is programs funded under Title V, the Maternal and Child Health Block Grant (MCHB), which requires performance measurement for contracting and evaluation. State welfare reform evaluators should collaborate with Title V program staff to explore data linkage, inclusion of common data elements of welfare status and health across data sets, and other ways to share data and evaluate child health in the era of reform. For example, several states, including Kansas and Arizona, are implementing performance measurement systems in their Title V maternal and child health programs (Gabor et al., 1997; Grason and Nachbar, 1997). In a pilot project involving seven states, sponsored by the MCHB in 1998, core performance measurements are monitored. These measurements include: needs assessments, percentage of Medicaid-eligible children enrolled, standards of care for women and children, health insurance coverage, and cooperative agreements among state Medicaid, WIC, and other human service agencies. An emphasis on information systems development is also part of these pilot programs and should be explored for linkage with welfare reform evaluation. In another example, the Institute for Child Health Policy at the University of Florida, Gainesville is currently evaluating enrollment in its Healthy Kids programs of outreach to uninsured children, as well as the quality of services in the program for children with special health care needs (Reiss, 1999; Shenkman, 1999).
Efforts to promote and monitor state health objectives should include indicators of children's health according to welfare, employment, and/or income status. As state and local communities plan for future Healthy People 2010 objectives, the impact of continuing welfare reform should be part of future health objectives. Where monitoring systems exist or are planned, they should include either linkage to state and local welfare data sets or common data elements that would provide for evaluation. For example, child health status measures could be monitored regularly according to the following categories: employed families with private health coverage, employed families with Medicaid or CHIP coverage, employed families with no coverage, unemployed families with Medicaid or CHIP, unemployed families with no coverage. These categories could be applied across a range of child health measures: prenatal care, infant mortality, low birth-weight, immunizations, hearing and vision screening, specialist care for children with special health care needs, injuries, or teen pregnancy.
The Aspen Roundtable on Comprehensive Community Based Initiatives has addressed the issue of using administrative data and identified several useful sources for conducting small-area analysis (Coulton and Hollister, 1999). These data include Head Start records, emergency medical service records, immunization registries, and hospital discharge records. Aggregate data at the neighborhood level, combined with comparable welfare data aggregated to the same level, can answer research questions about selected high-risk neighborhoods within a county, within major metropolitan areas, or across a state. Table 10-2 lists several Web sites of organizations conducting these types of neighborhood-level analyses using small-area analysis (Child Trends, 2000,b).
|Web sites for Local Research in Welfare Reform|
|United Way of Chittenden County, Vermont www.unitedwaycc.org||Chapin Hall Center for Children at the University of Chicago www.chapin.uchicago.edu|
|Social Assets and Vulnerabilities Indicators for Central Indiana (SAVI) www.savi.org||Center for the Study of Social Policy www.cssp.org|
|United Way of Central Indiana www.unitedwaycc.org||Community Building Resource Exchange of the Aspen Institute www.commbuild.org/|
|National Governors' Association www.nga.org||Aspen Institute Roundtable on Comprehensive Community Initiatives www.aspenroundtable.org|
|Urban Strategies Council Oakland, CA www.urbanstrategies.org||Zero Population Growth www.zpg.org|
|The Center on Urban Poverty and Social Change at Case Western Reserve University Povertycenter.cwru.edu/|
Examples of current research using administrative data on Medicaid use, health care access, and other health outcomes to evaluate the impact of welfare reform on children's health are increasing. In spring 2000, a three-state study about children's movement among AFDC, Medicaid, and foster care was released by the Assistant Secretary for Planning and Evaluation (ASPE) of the U.S. Department of Health and Human Services. The study was conducted by Chapin Hall Center for Children at the University of Chicago, Center for Social Services Research at the School of Social Welfare of the University of California at Berkeley, the University of North Carolina School of Social Work at Chapel Hill, and the American Institutes for Research (2000). The study used administrative data from 1995 to 1996 from AFDC, Medicaid, and child welfare programs, obtained through close collaboration with state agencies responsible for these program areas. A baseline population was identified and entry cohorts for each program were used to track experiences of children over the period just prior to PRWORA. The study focused on research questions about transitions from AFDC, including:
- Percentage of AFDC cohort that leave AFDC, by 1 year.
- Percentage of AFDC cohort that after 1 year transition to Medicaid only.
- Percentage of AFDC cohort that after 1 year exit the system (AFDC, Medicaid, and foster care)
- Among AFDC exiters at 1 year, the percentage who use Medicaid.
Wide variation was found in these measures across Illinois, California, and North Carolina. Differences also were identified for the four measures across children's age groups. This study provides an example of (1) the need to collaborate with other state agencies when using administrative data; (2) the importance of defining the population of study, in this case entry cohorts for 1 year prior to PRWORA with no AFDC/TANF enrollment in the previous 2 years; and (3) the difficulty of generalizing across local areas when studying the characteristics and consequences of welfare programs.
South Carolina has also developed linking capacity of administrative data called CHILD LINK (South Carolina Department of Social Services 1999). This state system links the following data sets: AFDC/TANF, food stamps, Medicaid eligibility, Medicaid payments, work support program data, child protective services, foster care, juvenile justice, alcohol and substance abuse, and wage data. The purpose is to better understand the Medicaid utilization for children after a parent becomes employed and to determine whether, after a client leaves welfare, they use other services to help them through the transition period.
Finally, an inventory of administrative data sets was prepared by UC Data Archive and Technical Assistance of the University of California at Berkeley (1999). This inventory was the result of surveying 26 states about their use of administrative data sets and their capacity to link them. Ninety-five percent of the 26 states were linking AFDC/TANF, Medicaid eligibility, and Food Stamp Program data. Fifty percent were linking AFDC/TANF, Medicaid claims, Medicaid eligibility, and Food Stamp Program data.
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