South Carolina CHILD LINK
Welfare Reform/Child Well-Being Administrative Data Linking
By South Carolina Department of Social Services
June 1999
The South Carolina Department of Social Services (SCDSS), along with its
partners, have been pleased with the success of the CHILD LINK Project and
will continue in the future to build upon its efforts.
Table of Contents
CHILD LINK enabled SCDSS and its partners to link the following databases:
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CHIPS
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Client History and Information Profile System. This database contains
administrative and payment information regarding both AFDC/TANF and Food
Stamps cases;
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CIS
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Client Information System. This system contains administrative information
regarding client eligibility for Medicaid services;
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Medicaid Services Payment System
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This database actually resides with another state agency, the SC Department
of Health and Human Services, and contains Medicaid payment data;
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Work Support (or WNAT)
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This database contains client data about work support eligibility, participation,
and services;
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TitleXX
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This system contains information about child and adult protective services
and foster care services;
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CPS
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Child Protective Services. The CPS system contains investigative
information on Child Abuse & Neglect cases;
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Foster Care Tracking
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This system contains information about foster children and their placements;
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State of South Carolina Masterfile
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This file contains all services for one calendar year from several health
and human service type agencies such as the Department of Juvenile Justice,
Department of Alcohol and Other Drug Abuse Services, and the Department of
Health and Environmental Control;
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Employment Security Commission (ESC) Wage Match
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This file contains quarterly wage information for all South Carolina employers
required to report wage data.
All of these files are statistical SAS databases that are individually stripped
off of the agencies legacy systems and linked statistically. Each file
is updated either monthly or quarterly (Medicaid Eligibility, Medicaid Payment
System, and the ESC information are updated quarterly) with the exception
of the states Masterfile. The information in the CHILD LINK warehouse
is only for those CHIPS clients who matched to this enormous population file.
The statistical warehouse stores historic information on all clients from
each of these systems so that SCDSS can measure change. In many ways, the
CHIPS system served as the primary "linker" file to which the other files
were linked. There are a couple exceptions. Because of the uniqueness and
the lack of identifiers in the Child Protective Services, SCDSS relied heavily
on the TitleXX number that caseworkers added to the legacy system. Thus a
more natural linkage was to link Child Protective Services first to TitleXX.
Likewise the Foster Care Tracking was first linked with the TitleXX system.
The TitleXX system was then linked to CHIPS. For the other data systems,
CHIPS linked directly.
CHILD LINK enabled SC to build software to extract identified data elements,
create update programs, and build software to link the files statistically.
Most importantly CHILD LINK helped SC to build up expertise in these data
systems fostering relationships between program specialists and researchers.
This linked database has enormously increased the capability in South Carolina
to examine a variety of issues. For example:
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By including employment information, we can examine employment patterns and
the job retention of our clients and changes in their quarterly wages;
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Because this information is also linked to the Medicaid files, we can explore
changes in Medicaid utilization after becoming employed. Because all clients
are tracked including children, we can further investigate the Medicaid
utilization for children after a parent becomes employed;
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By linking to the states Masterfile, we can review what other agencies
SCDSS clients access. As these clients leave the welfare rolls and the
states Masterfile builds historic information, we can check if utilization
patterns change. For example, as a client leaves welfare, do they access
other agencies more to help them through the transition period?
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Because all this information also is linked to the human services systems,
additional questions on child welfare can be asked. Do rates of abuse and
neglect increase as a client leaves welfare? Other questions regarding the
cycle of poverty can also be asked. Do former foster care clients become
TANF clients?
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Even more questions can be asked regarding impacts on other agencies. Are
children who are abused and/or neglected more likely to end up in the Department
of Juvenile Justice system?
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Additionally, CHILD LINK enabled us to geocode or address match our founded
child abuse and neglect cases to the Census Block Group. This allowed us
to add a further dimension by helping us to locate potential "high-risk"
neighborhoods.
As welfare reform continues to evolve and more clients leave the rolls, these
questions and many more are important. South Carolina believes it is critical
to ensure that there are few (if any) negative consequences to clients,
especially children.
SC is pleased with the implementation process. There are several structural
issues that contributed to the success of the project.
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For CHILD LINK, a Management Team was created which met regularly. Members
included key SCDSS researchers and upper management, program specialists
in the human services systems, our partners with the Department of Health
and Human Services and our partners with the Budget and Control Boards
Office of Research and Statistics (ORS). The management team served several
functions such as:
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Educating team members regarding the capability of a linked database;
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Providing the primary lead in brainstorming on possible analyses;
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Reviewing progress reports on the implementation issues;
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Utilizing the expertise in the management team to check for any biases; and
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Tracking progress and overcoming any obstacles.
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Our partnership with the SC Budget and Control Boards Office of Research
and Statistics (ORS) also contributed to the success of the project. ORS
functions as a service and research agency to state government. As part of
their on-going work with the SCDSS, they had already created a statistical
warehouse using the CHIPS system and had gained experience in dealing with
those administrative files. In addition, they also had experience in analyzing
and linking a number of administrative files to the Medicaid system and the
state Masterfile.
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As members of the Governors Cabinet, the SCDSS has a solid relationship
with the SC Department of Health and Human Services (SCDHHS). While a
confidentiality agreement was necessary to link the CHIP system to the Medicaid
system, that agreement was sketched out in a brief meeting with the CHILD
LINK lead coordinator, ORS, and SCDHHS. As noted before, SCDHHS was invited
to join the CHILD LINK Management Team. Use of the state Masterfile was similarly
permitted since the Governors Office controls its release. However
a confidentiality agreement had to be negotiated with the SC Employment Security
Commission. Because of ORSs position as a service agency, it was agreed
that the data should reside there.
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In the course of the CHILD LINK grant, a number of technical issues arose.
One particular issue was the conscious decision to link the files using various
combinations of known identifiers as opposed to probabilistic matching which
is extensively used in the research world. To check the validity of the matches,
multiple random samples were pulled and the matches reviewed. Because of
the lack of identifiers especially on the Child Protective Services database
and the lack of experience in using the Human Service files, it was agreed
that this was the proper course for SC. ORS, however in another project unrelated
to CHILD LINK, will be doing a comparison study of the more traditional approach
to probabilistic matching. It is expected that this comparison will provide
valuable insights.
A number of research products were initiated. The following lists some of
the issues under examination, a description of the process, and the results
of the research.
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Research Question: Do clients who leave TANF have a higher usage rate
of TitleXX and child welfare services?
Description of the Process: Using the linkage established between
the CHIPS system and the TitleXX system, ORS staff refined the information
to primarily focus on the CHILD population (children 0-17 years old). Staff
proceeded first by sub-setting the data set to children only. After that
step, children were separated into two further sub-populations: children
who have received AFDC/TANF and children who are in the Food Stamps only
population. Two populations were created: "Before TANF" and an "After TANF".
These two populations were followed for twelve months (controlling for
seasonality) in a longitudinal study to determine by comparison if the "After
TANF" population was more likely to incur higher rates of TitleXX services
and particularly those related to child abuse and neglect. In order to control
bias, both starting populations were controlled for previous TitleXX services
experience.
Results: While initial analysis suggests that the rate for the TitleXX
services did not appear to increase for the "After TANF" population, that
population needs to be continually studied and refined. The results of some
of this work were presented at The National Association for Welfare Research
and Statistics held in Chicago from August 2-5, 1998.
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Research Question: Are there particular neighborhoods with higher
than normal rates of abuse and neglect?
Description of the Process: From the Child Protective Services database,
a 3-4 year trend database of founded cases only was extracted. This trend
database was geocoded to the neighborhood level in order to locate "high
rates/numbers of abuse and neglect". Maps were produced statewide by zip
code showing absolute numbers and rates of children (rates were calculated
using a 1996 estimate of children by zip code). In addition, maps at the
neighborhood (census block groups) level were produced for Lexington, Richland,
and Newberry. For these neighborhood maps, both absolute numbers and rates
using census information were included.
Results: Results do indicate that there are neighborhoods with higher
than usual rates of abuse and neglect. This information was also shared with
another project "Safe Futures" which is a coalition of state and local agencies
in the Midlands area (four-county geographic region) concerned with youth
violence. The "Safe Futures" project used the abused and neglected maps along
with Department of Juvenile Justice information to target high-risk
neighborhoods. In additional several counties have requested to have their
TANF caseloads as well as their CPS founded cases be mapped. CHILD LINK has
enabled us to respond to those requests.
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Research Question: Has Medicaid utilization changed for any member
of a TANF household where at least 1 adult member has become employed?
Description of the Process: In this study, we began with all AFDC/TANF
cases that had closed for earned income. In order to provide adequate time
frames to detect differences in utilization and to control for seasonality,
the study population required 1-year of pre-employment activity and 1-year
of post employment activity. Therefore each of these cases must have been
an active AFDC/TANF case for at least one year prior to the closure date.
In order to be retained, the case must have had at least one adult earning
wages in the first and last quarters of the post closure year.
Because varying Medicaid Eligibility coverage can affect results, the Medicaid
Eligibility coverage was next examined for any biases. This study used a
working definition of Medicaid Eligibility coverage of 700 or more days of
Medicaid eligibility (2 years less 1 month). Claims essentially were divided
into three types: HIC (physician, clinic, and laboratory claims), Outpatient
(which includes both emergency and non-emergency room visits) and Inpatient
hospitalization. For HIC claims, only physician visits were included. Outpatient
claims were further sub-categorized as emergency and non-emergency visits.
In addition, outpatient and HIC claims were summed thereby providing an index
for ambulatory care utilization. For each claim type and combination of claims,
the number of paid claims for the pre-employment and post-employment periods
were summed. One way Analysis of Variance (ANOVA) with repeated-measures
factor was the tool selected to use for the analysis. This tool allowed for
the analysis of the number of Medicaid claims per individual filed one year
prior to employment versus the number of claims filed one year after employment.
In an attempt to control for natural changes in medical care utilization
as individuals age, the analysis was stratified by age.
Results: Our analysis finds virtually no support for employment effects
on Medicaid utilization by former TANF recipients. The evidence is weak and
inconsistent. The substantive differences among pre- and post employment
means is typically .2 claims per person and never exceeds .45 claims when
all claim categories are combined. Few of these differences are statistically
significant at the .05 level.
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Additional Uses of the Linked Databases: SC conducts a quarterly random
sample survey of its TANF Leavers. While the response rate to the survey
is excellent (for the interviews conducted during June, July, and August
1998, the response rate was 76%); there is of course concern on the well
being of the remaining percentage of clients. To locate these "unavailable"
clients, ORS linked all adult household members of the TANF Leavers survey
to the ESC Wage match. For Waves 1 and 2 of the TANF Leavers survey, ORS
linked overall 67% of the clients to the ESC files where the client had wages
after the surveys interview date. Of those clients who completed the
survey, the match rate was 71% (for not completed: the match rate was 55%).
The "not completed" category breaks down into three sub-types: no answer,
unavailable, and refused. Their corresponding match rates were 69% (no answer),
44% (unavailable), and 81% (refused). In addition to looking at match rates
by the various interview result categories, ORS also calculated average number
of quarters with wages greater than $0, average wages earned in the last
quarter and the average number of jobs in the last quarter. To examine if
there were any significant differences, ORS performed several T-Tests on
differences of the means. The results showed no significant differences in
average wages earned last quarter among the various categories of clients.
Using the statistical warehouse, SCDSS plans to study two particularly important
populations in the near future. One such population is all sanctioned clients.
Another population would be the abuse and neglected "founded" cases. In the
latter study, we would link to the emergency room and hospital databases
to determine if we could have predicted in advance these abuse and neglected
cases.
A number of products were produced as a result of the CHILD LINK project.
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Details of the linkage, methodology, and preliminary results were presented
at The National Association for Welfare Research and Statistics held in Chicago
from August 2-5, 1998.
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While not formally presented or published, a paper was written on the results
of analysis on Medicaid utilization before and after employment. (See attached)
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A workshop on the capabilities of the CHILD LINK statistical warehouse is
being prepared for all SCDSS upper management, research, and county director
level staff. It is envisioned that through this workshop, new ideas on the
potential used of this warehouse will be brainstormed.
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The success of CHILD LINK in creating a statistical system helped position
SCDSS in furthering its research goals in the TANF and Food Stamp Leavers
grants.
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A number of maps and printouts were distributed to SCDSS management, policy
and program specialists and County front-line staff. Some examples include:
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An analysis on Foster Care children who left Foster Care (where their case
closed but had not aged out), who later reappear as Foster Care cases and/or
Child Protective Services cases.
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An analysis on children who aged out of the Foster Care system to determine
how many later reappeared on CHIPS as a TANF or Food Stamps case and/or were
tracked in the ESC Wage Match file.
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Maps (and printouts) showing TANF cases with Founded Abused and Neglected
Cases at the Neighborhood level (Census Block Group) for several counties.
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Maps showing Founded Abused and Neglected Children and Violent Juvenile Justice
children at the Neighborhood Level (Census Block Group) for several counties.
SCDSS is planning to continue to maintain and expand the linked database
in the future.
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In addition to its continually relationship with ORS, SCDSS has been notified
of receipt of two additional grants focusing on TANF and Food Stamp Leavers.
In the TANF Leavers project, we plan to expand and enrich our current survey
on clients who have left the welfare rolls and have not returned. We will
also create a longitudinal database by revisiting former clients thereby
enriching our knowledge on their well being. This longitudinal database and
the results of the expanded survey will be linked to the rest of the statistical
warehouse.
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In addition to the TANF Leavers project, we will be expanding our survey
instrument to include Food Stamp Leavers. Again the results of this effort
will be linked to the full statistical warehouse. In addition as part of
the Food Stamp Leavers project, we anticipate using the statistical warehouse
to complete an administrative study.
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During the CHILD LINK period, SCDSS was building a new human services system
(known as SACWIS). While too late to be built into the CHILD LINK work, SCDSS
has plans to incorporate the new database into the statistical warehouse.
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National Association for Welfare Research and Statistic Presentation, August
2-5, 1998
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Medicaid Utilization: A Comparison between
Pre- and Post-Employment
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Maps showing number of abused and neglected children in specific counties
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Graphs and charts showing the percent of AFDC/TANF children receiving foster
care and protective services
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Report of a survey of TANF "leavers"
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