Assessing the Field of Post-Adoption Services:
Family Needs, Program Models, and Evaluation Issues: Analysis of Secondary Data

2 Adoption Dissolution, Disruption, and Supports
in North Carolina

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Contents

• 2.1 North Carolina Administrative Data
• 2.2 Study Population
• 2.3 Adoption Displacement or Dissolution
  • 2.3.1 Data for Studying Dissolution
  • 2.3.2 Adoption Dissolution and Displacement in North Carolina
• 2.4 Adoption Disruption
• 2.5 Adoption Subsidy and Vendor Payments for Adoptive Families
• 2.6 Summary

These analyses of administrative foster care and adoption data address adoption disruption and dissolution as well as subsidies. Their purpose is, in part, to gain some insight into the adoption and subsidy dynamics in North Carolina. More fundamentally, however, they are intended to demonstrate the strengths and limitations of research methods in states whose approach to storing administrative data is similar to that of North Carolina and to determine what additional information might need to be collected and stored in order to refine these analyses. The data files used for this work are maintained by the North Carolina Department of Social Services and cover the last 10 years.

2.1 North Carolina Administrative Data

Four different administrative data files maintained by the North Carolina Department of Social Services provided data for the analysis files used to examine adoption dissolution, adoption disruption, and adoption assistance in North Carolina. To define the population of children to be included in this study, three data files were merged: (1) summary information on each child receiving adoption assistance, (2) vendor payments made to other post-adoption service providers in the name of adopted children, and (3)records of adoption subsidy checks. The summary child-level file was first merged with the adoption subsidy check record file, and then information on payments to vendors was added into this merged file. The total number of unique ID numbers in this merged file was 12,067. Exhibit 1 summarizes the number of unique ID numbers in each data file.

Since there are no records in the payment files prior to January 1990, children with a final order of adoption before January 1, 1990, or who had no information on the date of the final order were identified and deleted from the final analysis file, leaving a possible 8,647 children in this file. Our next step was to assess the quality of this data merge based upon DSS-assigned ID numbers.

Assignment of multiple ID numbers complicates analysis of adoptions.

In North Carolina, children adopted from the public child welfare agency may have up to three different ID numbers. The first ID number, the foster care ID number, is assigned when a child initially enters out-of-home placement. After the adoption decree is final and if the child is to receive adoption assistance, a second ID number is assigned to track these payments. Finally, should an adoption dissolve and a child reenter out-of-home placement, a third ID number may be assigned. To further complicate these analyses, if a child receives adoption assistance in the form of reimbursement for nonrecurring costs prior to the final decree of adoption, the payments are recorded under the foster care ID number. After the adoption is final, the child may receive cash assistance and/or vendor payments recorded under the second ID number. Given the confidentiality of the adoption process, multiple ID numbers for the same child are not linked, making it impossible to assess the experiences of children across the continuum of adoption events.

To address these issues, even though it is possible that adopted children received additional assistance under the foster care ID number, we limit our analyses of adoption assistance to cash assistance and vendor payments that occur after the final decree. Additionally, we developed an algorithm to assess whether there were children with multiple ID numbers in this study population. We identified 182 pairs of ID numbers for children with the same gender, birth date, and date of final adoption decree. Since this number was so small, less than 4 percent of the study population, it appears that our restriction algorithm for study inclusion effectively resulted in a mostly unduplicated count of children. Exhibit 2 summarizes the source of information for the 8,647 children in the final study population. All but 340 children in the final data set had a record of either receiving a cash assistance payment or a vendor payment made in their name. Over half of the children received both.

After using the vendor payment and adoption assistance data files to identify the study population and to analyze patterns of adoption subsidy, we accessed one additional source of information, the North Carolina longitudinal foster care placement data files. These files contain information on all children placed in out-of-home placement in North Carolina since the mid-1980s. The placement data files when linked to the cash assistance data provided the data necessary for studying adoption dissolution. Additionally, the placement data files provided data for the adoption disruption analyses. Exhibit 3 summarizes the source of data for each topical area under study. The results of the analyses are described in the sections that follow.

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2.2 Study Population

There were 8,647 children in the study population. All children had a final decree of adoption between January 1, 1990, and July 15, 2001. Exhibit 4 summarizes the demographic characteristics of the group. Only 12 percent of the children were older than 11 at the time of the final decree of adoption. There were slightly more boys than girls, and more than half of the adopted children were members of minority groups. A large percentage of the children, 90 percent, were in open cases and currently receiving some form of adoption assistance. Virtually all of the children (99.8 percent) were identified as emotionally disturbed, which meets the adoption assistance eligibility requirement for "special needs." It is unclear whether these children were considered emotionally disturbed on the basis of having been in foster care, or whether there were particular criteria that children met in order to be given this classification.

Although there are some children in the study who were adopted in the early 1990s, almost three-quarters of the children in this study, 70 percent, were adopted in the past five years. Exhibit 5 provides a summary of the number and percentage of children by the year of final adoption decree.

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2.3 Adoption Displacement Or Dissolution

2.3.1 Data for Studying Dissolution

North Carolina enters information on adoption assistance payments into its payment databases but does not identify adopted children within its foster care files. However, by combining adoption subsidy and foster care placement data, we can establish a cohort of adopted children, who can then be studied like other cohorts to determine if they subsequently have a new placement. A voluntary placement may indicate a post-adoption services displacement episode rather than a dissolution. An involuntary placement would be more likely to be a dissolution than a displacement, although these involuntary placements could also be made — depending on the locally administered rules — for children of parents who retain legal custody of them. Termination of parental rights (TPR) of the adoptive parents would represent a less ambiguous indicator of dissolution, but this event was not available from the files available for analysis. Without integrating data on the legal relationship between parent and child, the differences between dissolutions and displacements are not possible to determine. Although UNC currently has been given limited access to use North Carolina foster care data for this exploratory effort, we have so far only requested permission from the state to use the foster care data and the subsidy data. We have not requested the use of the data collected during the processing of adoption cases, which includes substantially more information about the adoption circumstances. Exhibit 6 shows the key dissolution and displacement questions and the possibility of answering them with the data that we are likely to be able to access.

Exhibit 6.
Key Questions for Dissolution Analysis and Likely Data Access

Questions	Comments
What percentage of adoptions has a subsequent spell in care?	Although case ID numbers changed when an adoption was finalized, by linking these new ID numbers with the placement data files, we were able to determine whether children have entered care from an adoption — especially since the inception of the related AFCARS reporting requirements.
How many have a subsequent spell that is voluntary?	A code in the NC data file can determine if new admissions are court mandated or voluntary, help determine the characteristics of a child's replacement into care following adoption, and distinguish between displacements and dissolutions.
What is the duration of elapsed time before this subsequent spell begins?	If we can identify children who reenter care, then we can identify all the elements needed to conduct event history analysis.
What case characteristics (e.g., race and age at the time of adoption) are associated with a subsequent spell?
How do subsequent spells end (e.g., in reunification to the adoptive family, in no reunification, in a subsequent adoption)?

2.3.2 Adoption Dissolution and Displacement in North Carolina

We used two lines of analyses to examine adoption dissolution in North Carolina. First, we tried to track our cohort of adopted children to see if they experienced an out-of-home placement after the final decree. Second, we looked at all children who had entered out-of-home placement since July 1, 1998, to determine whether a child was previously adopted. Although neither line of analysis was entirely satisfactory, both provided information about possibilities for further research. Each is described below.

Cohort analysis. Because names of children were not included in our analysis files, we had to rely on the ID numbers to determine whether a child experienced a subsequent out-of-home placement after adoption. For a reentry to placement by a child receiving cash assistance payments to be considered an adoption dissolution, three conditions had to be met: (1) the date of entry to out-of-home placement occurs at least 90 days after final adoption decree date, (2) adoption assistance was no longer being received after this placement, and (3) if permanency was achieved at end of this placement, it was achieved with someone other than the primary caregiver at the time of the previous adoptive placement. This is the closest semblance we have to being able to define a dissolution, without having court records to establish the final outcome of the adoption. Of the 8,647 children in the adoption assistance data file, 2,217 were also in the placement data file, indicating that these children could have experienced a dissolution. Further analyses identified 70 children who met the adoption dissolution criteria that we established for these analyses. The remaining 2,147 placements, which did not meet all three criteria, represent out-of-home placements that did not result in dissolutions.

Delays and inconsistencies in assigning new client identification numbers for adoptive children who are receiving cash assistance resulted in the original overestimate of potential dissolutions. This is an indicator of the challenges of using administrative data for studying this issue. There were 2,217 children whose child welfare system ID numbers were in the placement data file but the identified child did not meet one of the three criteria that we set out for an adoption dissolution — i.e., placement date after the adoption, no longer receiving adoption assistance after the placement, or exit reason suggests reunification with primary caregiver at time of placement. These cases are difficult to interpret. They underscore the importance of treating these analyses as preliminary work that demonstrates the use of data to study post-adoption experiences and services rather than presenting firm conclusions about the number of dissolutions/disruptions in North Carolina.

Exhibit 7 summarizes age at adoption, race, gender, and year of adoption for the approximately 1 percent of children who experienced a dissolution — by the aforementioned criteria — compared to those who did not. Even these criteria are not airtight, however, as a child who is still adopted could — in very rare instances — be placed into guardianship with another member of their family.

Exhibit 7.
Characteristics of Children Who Experienced an Adoption Dissolution and Likelihood of Dissolution

	No dissolution	Dissolution	RR
Age at adoption
Birth to 5	4,381 (99.6%)	17 (0.4%)	1.0
6 - 11	3,231 (98.8%)	38 (1.2%)	3.2(1)
12 - 15	809 (98.2%)	15 (1.8%)	6.2(1)
16 - 17	156 (100%)	0 (0.0%)	.1
White	3,815 (99.4%)	24 (0.6%)	1.0
Black	3,870 (99.1%)	37 (0.9%)	2.0(2)
Other	892 (99%)	9 (1.0%)	2.2(3)
Male	4,402 (99.4%)	28 (0.6%	1.0
Female	4,175 (99.0%)	42 (1.0%)	1.5
Year of adoption
1990 - 1995	2,124 (98.5%)	33 (1.6%)	1.0
1996 - 1998	2,639 (98.8%)	31 (1.2%)	.65
1999 - 2000	3,809 (99.8%)	6 (.2%)	.35
1 p < .001 2 .001 < p < .01 3 .01 < p < .05

Older children (current age) and minority children appear to be slightly more likely to experience an adoption dissolution. While statistically significant, these analyses are based on a small number of cases and should be viewed with caution.

Using Cox Proportional Hazards Models, we estimated the risk of adoption dissolution, shown in the final column in Exhibit 7, by age at adoption, race, gender, and year of adoption. Older children (current age) are significantly more likely to experience dissolution than younger children. Children who are 6 to 11 years old at adoption are three times as likely to experience dissolution than infants while young teenagers are over six times as likely. The risk of adoption dissolution in North Carolina is low for all children. However, compared to white children, black children are twice as likely as white children to return to placement after an adoption.

The following chart (Exhibit 8) provides a summary of the number of days between the final adoption decree and subsequent placement into out-of-home care for the 70 children that we identified. It shows that about 50 percent of these dissolutions occur within three years of adoption.

Exhibit 8.
Length of Time Until Dissolution

These merged data may or may not provide valid estimates of children who return to placement after being adopted. The findings of a less than 1 percent dissolution rate in North Carolina must be viewed cautiously. Since the population of adopted children who we are able to include in these analyses is limited to those receiving cash assistance payments, it is possible that the dissolution rate is low because these are among the most stable adoptive relationships. This would suggest that the study population did not include a substantial group of adopted children who are the most likely to disrupt. However, this seems unlikely for a few reasons. First, conversations with state officials in North Carolina indicated that they believe most adopted children in the state receive cash assistance payments and, thus, would be in our study population. In addition, comparisons of the number of children adopted in North Carolina over the past several years and the number of children receiving adoption subsidy payments during the same time period supports the conclusion that these analyses represent the appropriate universe of adopted children.

It is also possible that these data and our linking algorithms do not validly identify all adoption dissolutions. It is likely that most children who reentered placement subsequent to adoption did so under a different ID number, either the foster care number or a newly assigned number. Since the policy in North Carolina is not specific in terms of which ID number to use for a reentry following an adoption, it is not surprising that these data are not definitive, at this point in time, for these analyses.

A third possibility is that these data actually represent what is going on in North Carolina. The state's rate of reentry to foster care is far better than the national average, suggesting that a low rate of adoption dissolution may also be plausible.

Even though this line of analysis did not produce the results that we expected, if new ID numbers were systematically and consistently assigned to all children in the state who were adopted, this approach could be useful in understanding the course of an adoption that ultimately fails.

Older children and white children are more likely than others to reenter care after adoption

Entry into foster care. The North Carolina longitudinal placement data files provided the source of data for the second line of adoption dissolution analysis. In July 1997, as part of the AFCARS enhancement, North Carolina added a data element to the placement data files that recorded whether a child who was entering out-of-home placement had been previously adopted. Newly updated longitudinal data files created in April 2002 contained information on placement experiences of children who had entered placement through December 2001, providing a minimum of four and a half years of data for the new AFCARS data elements.

Of the children entering placement between July 1997 and December 2001, 318 had been previously adopted. Exhibit 9 summarizes the characteristics of legally adopted children who entered placement. Over half were teenagers; 58 percent were white; and 51 percent were female. Compared to the characteristics of children not previously adopted who initially entered placement during the last 10 years, previously adopted children entering placement were more likely to be white (56 percent versus 47 percent) and teenagers (66 percent versus 26 percent).

Exhibit 9.
Characteristics of Children Entering Placement Authority after July 1997 by Previous Adoption

	Children with previous adoption entering care		Children not previously adopted entering care
	#	%	#	%
Age (yrs) at entry to placement following adoption
Birth to 5	25	9	10,943	46
6 - 11	83	26	6,487	27
12 - 17	210	66	6,253	26
White	185	58	11,158	47
Black	111	35	9,669	41
Other minority	22	7	2,888	12
Male	155	49	11,870	50
Female	163	51	11,842	50

Not all legally adopted children who entered placement authority experienced adoption dissolution, as shown in Exhibit 10. About one-third of the children were reunified with their primary caretaker or exited placement to a parent other than the parent who originally lost custody of the child, a guardian, or a court-appointed caretaker; 17 percent left for unknown reasons or miscellaneous other reasons; 16 percent were adopted; and 10 percent were emancipated; leaving slightly over one-fourth still in placement in April 2002.

Although these analyses do not provide sufficient data to calculate a dissolution rate, they suggest a higher level of dissolution than seen in the cohort analysis. The analyses provide some insight into the number of adoption dissolutions that occur per year and the characteristics of children who are reentering placement following an adoption.

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2.4 Adoption Disruption

Using the foster care placement files, we next examined the subject of how many children experienced an adoption disruption, that is, had placements coded as an adoptive home but ultimately were not adopted. There were 54,747 children who initially entered placement in North Carolina from July 1, 1989, through June 30, 2001. The North Carolina longitudinal placement data files track all placements experienced by these children. There were 463 children who had a first placement recorded as an adoptive home. A full 77 percent of these children subsequently exited placement to adoption. Only 5 percent of these first placements were still in the placement authority of the state when the files were created. The remaining 18 percent of children might have experienced disruptions in adoptive placement or had changes in their adoption plans for other reasons, including reunification, emancipation, running away, or a conversion to a guardianship. At this time, we cannot determine the ultimate case status of these children who had an adoption plan. North Carolina did not record all of these exit reasons until July of 1997, when they added this feature in order to meet their AFCARS requirement. Thus in future years, this information about children who had an adoption plan, but were not adopted and no longer have such a plan, will be available.

A larger group of children (2,657) entered foster care for reasons other than adoption but were subsequently in a home that was identified as an adoption placement. The majority of these children (59 percent) have subsequently exited placement to adoption; another 10 percent were still in the placement authority of the state, very possibly still en route to adoption. This leaves 31 percent of children who had an adoption plan — at one time — but no longer have one. Again, this group could include some adoption disruptions, but is also likely to include many more children who left the placement authority of North Carolina for other reasons. We cannot determine the difference.

The apparent imprecision in recording of the pathway to adoption is also demonstrated by the finding that the majority of children (65 percent) who achieve permanency through adoption are never placed in an identified "adoptive home." These are most likely foster children who are adopted by foster parents without ever having been identified in the data system as changing status from foster to adoptive homes. This suggests that case plan goals are often not updated in a complete or timely fashion — this is a common finding in research using administrative foster care data systems. Taken together, then, the data do not support an effort to precisely estimate adoption disruption rates in North Carolina. They do indicate, however, that this will become more possible in future years.

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2.5 Adoption Subsidy and Vendor Payments for Adoptive Families

These analyses use data that record payments to adopted children (subsidies) or payment for services received by adopted children (vendor payments). These vendor payments may be used to purchase such services as respite care, therapeutic summer camp, and specialty mental health or educational services. Since the information is tracked by the adopted child's client ID number, the quality and completeness of the data are dependent on this data element. In North Carolina, adopted children receive a new client ID number after the adoption decree is final, making it impossible to track total expenses for children across their entire child welfare career. Thus, these analyses focus solely on the amount of assistance that a child receives after the final adoption decree.

Nearly all adopted children receive subsidies, which are generally stable over time.

Because 94 percent of the children in this analysis file received cash assistance payments at some point in time and these payments can only begin after the final adoption decree is entered, it is our assumption that the ID numbers represent payments to unique children and that a single child will not have two ID numbers while receiving cash assistance. To the extent that this assumption is incorrect, we may be over-counting the number of children receiving adoption assistance payment. A comparison of the number of foster children adopted in North Carolina in the past six years, 6,122, to the number of children with a final adoption decree in the last six years who are included in these assistance files, 6,182, suggests that there may be a few children with multiple ID numbers in the data files. These are probably not enough, however, to change the result of these findings in any major way.

Exhibit 11 summarizes the timing and amount of assistance received by adopted children in North Carolina since 1990. Almost all children with adoption assistance received cash payments (94%), and close to two-thirds (61 percent) also received additional assistance in the form of payments to vendors for therapeutic or medical services or nonrecurring costs of adoption. Half of the children started receiving cash payments almost immediately after the final decree. Within six months of the decree 96 percent had received their first cash assistance check. The average cash payment amount during this time period was $346 per month received for an average of 42 months. However, because most of these cases are still open, these averages may change over time since there are some increases in payments as children age. Very young children received average cash assistance payments equal to $315; the average payment for children between 6 and 12 years old was $364; for children older than 12 the average payment increased to $409.

Slightly over half (51 percent) of children had no change in their subsidy amounts over the course of their assistance period. For the remaining children, many of them having been adopted for relatively short times, the increases were not substantial. This resulted in an average difference between the initial and last or most recent payment equal to $32. Exhibit 12 provides more detailed information about the length of time children receive subsidy payments in North Carolina in relation to subsidy increases. These analyses suggest that there are relatively few increases during the first few years of the subsidy and that the subsidy changes peak after four years.

Exhibit 12.
Patterns of Increases in Subsidy

The average time between the first cash payment and the initial increase is almost two years; however, this varies by the age and race of the adopted child, as shown in Exhibit 13. This exhibit suggests that older children are less likely to receive subsidy increases and that the initial increase does not occur as quickly as it does for younger children. This is not surprising since the most frequent type of increase in subsidy amount in North Carolina seems to be tied to the age of the child and appears to parallel the increases that other foster children receive — increases that become less frequent as the child ages. These analyses, however, are perhaps somewhat misleading, since older children actually have less time in which they are eligible to receive assistance. To account for differences in eligibility time, using survival analysis we calculate the probability that a child will receive an increase.

Exhibit 13.
Patterns of Subsidy Increases by Child Characteristics

	Average no. of months between 1st payment and initial increase	Percentage with at least 1 increase	Avg. no. of increases for those with increase
Age (yrs) at 1st payment
Birth - 5	19.4	59%	2
6 - 12	24.5	44%	2
13 - 17	26.9	18%	2
Male	22.1	46%	2
Female	22.6	45%	2
White	22.6	48%	2
Black	21.9	46%	2
Other minority	23.7	35%	2

Survival analysis techniques make maximum use of available data by including all eligible children in the analyses whether they have already received a subsidy increase or not. Since most of the study population are active cases, it is possible, even likely, that many of the children who have not yet received a subsidy increase will eventually receive one. Survival analyses estimate this likelihood by calculating the cumulative probability that the event of interest, in this case, increase in subsidy amount, occurs by specific time points. Exhibit 14 estimates the overall probability that an increase will occur at a given time after first subsidy receipt. Exhibits 15 and 16 provide this probability estimate for children by age and race, respectively.

Exhibit 14.
Probability of an Increase in Cash Assistance

Exhibit 15.
Probability of Increase in Cash Assistance, by Age

Exhibit 16.
Probability of Increase in Cash Assistance by Race

Children who receive subsidies at young ages are most likely to receive increases

The overall cumulative probability of an increase is depicted in Exhibit 14. During the first year of assistance about 20 percent of children are likely to receive an increase; by the two-and-a-half-year mark the probability increases to about 50 percent. The probability of an increase varies by both age and race, as shown in the following two exhibits. Children under five years of age were the most likely to have subsidy increases and to incur them more quickly as indicated by the slope of the curve. By the one-year mark there is an increase in subsidy amount for an estimated 30 percent of young children compared with 20 percent of 6- to 12-year-olds and 10 percent of teenagers. Four years after the initial subsidy payment approximately 10 percent of children adopted before age 5, 40 percent of adopted 6- to 12-year-olds, and almost 70 percent of those adopted as teenagers are receiving the same subsidy payment. Because teenagers are aging out of the adoption assistance programs, these results are not surprising.

Because many factors are related to the length of time until an increase occurs, survival analysis was used to examine the relationships. Exhibit 17 presents the results of a Cox proportional hazards model that analyzes the likelihood that a subsidy increase will occur while controlling for characteristics of adopted children and length of eligibility time. Race and age at initial payment are significantly related to the likelihood of a subsidy increase. Even though the model controls for the number of months of assistance, children who begin receiving adoption assistance before age five (the reference group) are much more likely to receive increased subsidy payments than older children. Other minority children are less likely to receive an increased subsidy than either white (the reference group) or black children.

Exhibit 17.
Likelihood of Increased Subsidy Amount

	B	Sig.	Exp (B)	95.0% CI Exp (B)
				Lower	Upper
Gender	-.014	.660	.986	.926	1.050
Race		.038
White (reference group)					1.000
Black	-.054	.115	.948	.887	1.013
Other minority	-.146	.018	.864	.766	.975
Age 1st payment		.000
0 - 5 yrs (reference group)					1.000
6 - 11 yrs	-.614	.000	.541	.506	.579
12 - 17 yrs	-1.100	.000	.333	.277	.399
Months of payments		.000
0 - 36 (reference group)					1.000
37 - 72	.401	.000	1.493	1.366	1.632
73 - 108	1.406	.000	4.082	3.711	4.490
Over 108	1.568	.000	4.799	4.195	5.490
# Vendor checks		.000
0 (reference group)					1.000
1	.061	.137	1.063	.981	1.152
2 - 10	.252	.000	1.287	1.188	1.395
Over 10	.158	.009	1.171	1.040	1.319

Analysis of vendor payments indicated that half of the children with a vendor payment had the first payment within two months of the adoption decree and 74 percent had first payment within six months of the decree. The average number of vendor payments per child was four, with amounts ranging up to $2,000. The analysis of these payments is complicated by the fact that children could receive these payments before and after the final decree, and thus payments for one child could be recorded under different ID numbers. Thus, it is likely that these numbers actually underestimate the amount of vendor payments incurred by an individual child.

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2.6 Summary

These analyses serve multiple purposes. First, the analyses provide substantial instruction about the way that adoption data may be organized and some possible strategies for gaining information from them. In North Carolina adoption data are maintained in the foster care system (which indicates whether or not children placed into foster care had ever been adopted and whether children leave to adoption), in a payment system (which indicates whether there have been subsidies or vendor payments), in special manualized systems (for particular programs like those for HIV-affected children), and in the adoption information system (which contains information about the adoptive family and the circumstances of the adoption). The finding that the adoption data are in several places may be more typical than unusual, although work with more states will be required before determining whether any state has a typical system. North Carolina's data does not allow for a precise estimation of adoption dissolutions or displacements. To accomplish this, several adjustments would need to be made in the way data about reentries into foster care from adoptive families are collected.

Analysis of disruptions could also be improved if more specific information were collected about the reasons that adoption plans were terminated. The utility of this improvement would depend, ultimately, on how comprehensively adoption plans were identified in the data. If adoption plans are not recorded in a consistent and timely way, then timely information about disruptions of plans that do occur cannot tell the total story. We believe that many states currently lack the capacity to accurately record case plans.

These analyses suggest methodologies that could be useful in other states.

These analyses also demonstrate analytic methodologies that could be used to explore these issues in other states. Moreover, they highlight the critical need to consistently assign identification numbers at various points in time across the placement-adoption time continuum. It is possible to link multiple data files only when there is confidence in this process.

Equally important, the analyses provide substantive information about children who receive adoption assistance and describe the continuity of support provided by these important programs to adopted children in North Carolina. The analyses suggest that most adopted children in North Carolina receive some form of cash assistance support. Cash payments begin very soon after the final decree is entered and usually continue until the child reaches the age of 18. Although this report does not provide analyses of other sources of support for families with adopted children in North Carolina, it is important to acknowledge these here. In addition to cash assistance payments, North Carolina provides special supplements for adopted children with HIV and for children with substantial functional impairments. Because these programs have special requirements and payment structures, their accounting is not automated. Thus, they are not included in these analyses. North Carolina also makes all children who are adopted (except those with their own income) Medicaid eligible. In addition to the cash assistance payments, the state provides support to adoptive children in the form of vendor payments to cover the cost of special services, especially counseling and medical services when Medicaid coverage is exhausted.

Another area of analyses examines the likelihood that an adoption in the state will dissolve or disrupt. Because these analyses try to adapt data historically collected in legacy systems for administrative purposes, the data for these analyses are more tenuous than the adoption subsidy data. North Carolina has a low reentry to out-of-home placement rate so it perhaps should not be surprising that the adoption dissolution rate is also extremely low. Problems with the assignment of new client identification numbers and the inconsistency of these data across the state's 100 counties suggest that the state should undertake additional training and analyses to better understand adoption dissolution in North Carolina.

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