Market-based disparities in foster care outcomes

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Children and Youth Services Review 30 (2008) 388 – 406 www.elsevier.com/locate/childyouth

Market-based disparities in foster care outcomes William Meezan a,⁎, Bowen McBeath b b

a College of Social Work, Ohio State University, United States School of Social Work and Division of Public Administration, Portland State University, United States

Received 29 August 2007; accepted 10 October 2007 Available online 16 October 2007

Abstract Managed care and performance-based contracting in state child welfare systems have appeared as a consequence of the increased attention that federal and state policymakers are paying to system performance and service costs. This study reports findings from a longitudinal natural experiment that examined the effects of a performance-based, managed care contracting mechanism on foster care outcomes. Multivariate analyses identified market-based disparities in some of the outcomes experienced by foster children: controlling for child, family, and caseworker characteristics, children served by agencies with performance-based, managed care contracts were less likely to be reunified and more likely to enter kinship foster homes, when compared to children served by agencies reimbursed through fee-for-service contracts. Analyses also suggested that there were few other variables consistently associated with foster care outcomes. These results call into question the evidentiary basis for the diffusion of managed care and performance-based contracting in the child welfare sector, and suggest that state child welfare systems ensure that foster care placement decisions are influenced more by child and family needs than by financial considerations. In addition, they suggest that managed care and performance-based contracts should include specific financial incentives for family reunification. © 2007 Elsevier Ltd. All rights reserved. Keywords: Foster care; Market-based systems; Outcomes; Managed care

1. Introduction Since the passage of the Adoption and Safe Families Act in 1997 (PL 105-89), state child welfare systems have been pressured to identify innovative service models that move foster children out of state custody efficiently without compromising their safety or well-being. Particularly in the wake of the first round of Child and Family Service Reviews, in which no state successfully met all 14 federal outcome and systemic benchmarks (Children's Bureau, 2007), states now have significant incentives to improve the performance of their child welfare systems if they are to avoid financial penalties. In this performance-focused environment, 24 states have received federal Title IV-E waivers to implement demonstration projects that reorganize child welfare service delivery. Some of these waivers have sought to alter the financing of foster care for a variety of purposes (James Bell Associates, 2007).

⁎ Corresponding author. E-mail address: [email protected] (W. Meezan). 0190-7409/$ - see front matter © 2007 Elsevier Ltd. All rights reserved. doi:10.1016/j.childyouth.2007.10.011

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A few state child welfare initiatives have sought to adapt market-based models from the business, health care, and medical sectors for use in their child welfare systems (McCullough & Schmitt, 1999, 2000; U.S. GAO, 1998). This growing experimentation with financially-driven models such as performance-based contracting and managed care is symptomatic of a broader trend of marketization in child welfare, through which child welfare agencies have sought to incorporate efficiency-based models and practices from the private sector. In addition, managed care and other marketbased contracting mechanisms have become increasingly common in other sectors that impact child welfare-involved children and families, including the physical health, mental health, and substance abuse sectors (Mechanic, 1999; Smith, 2002). In these efficiency-driven models, state child welfare financing has become strongly linked to child and family outcomes (Wulczyn, 2000a, 2000b, 2005). It has been assumed that the incorporation of market-based approaches into child welfare systems will result in demonstrable cost savings and improved performance through a reduction in the number of foster care placements, improved rates of achievement of various permanent outcomes, improved time to achievement of permanent outcomes, fewer replacements while in care, and lower rates of recidivism upon exit from foster care. Managed care and performance-based models are generally thought to improve these outcomes by rewarding service providers that limit unnecessary, duplicative, and untimely service provision and, conversely, by penalizing agencies that fail to reach performance targets (Planning and Learning Technologies, Inc. and The University of Kentucky, 2006). The usefulness of these models has recently been questioned, however, by evidence of their inconsequential effects on child outcomes in some states (James Bell Associates, 2007) and the considerable reduction in service provision to foster children and their families in performance-based, managed care environments (McBeath, 2006; McBeath & Meezan, in press; Snowden, Cuellar, & Libby, 2003) and to child welfare-involved children in Medicaid managed care environments (Rachavan et al., 2006). The results of these studies lead to questions as to whether market-based models are appropriate for child welfare populations. 2. Literature review 2.1. Effects of market-based models on foster care outcomes Market arrangements such as managed care and performance-based contracting may influence permanency outcomes by altering the financial risks and rewards faced by child welfare agencies. In the child welfare sector, most nonprofit agencies contracting with the public sector operate under fee-for-service contracts. In such a contracting environment, nonprofit agencies are reimbursed from public funds each time they provide a particular service or bundle of services to clients over a set period of time (Wulczyn, 2000a). Thus, agencies are guaranteed revenues if contracted services are delivered. In contrast, managed care and performance-based contracting models increase the level of financial risk that child welfare agencies bear. Managed care models reimburse agencies for services in a manner that is expected to contain costs (Embry, Buddenhagen, & Bolles, 2000; Wernet, 1999; Wulczyn, 2000a; Wulczyn, 2000b). Under capitated managed care frameworks, service providers receive a monthly, preset amount per client; case rate-based managed care models provide agencies with a predetermined amount for serving a client over a predetermined period, usually either a preset number of months or a spell in care (Westat, 2002). Thus, in managed care systems, child welfare agencies are guaranteed a profit only if they provide services for an amount less than a preset amount. Agencies therefore maximize their revenues if they serve clients in the most efficient, least costly manner. In performance-based contracting, revenues received are a function of agencies' ability to reach contractually-specified objectives related to either service delivery or client outcomes (Hatry, 1999; Wulczyn, n.d.). Agencies thus have a clear financial interest in reaching these objectives, since they are rewarded through payments based on their performance. Eleven of the 24 Title IV-E demonstration projects can be classified as containing market-based models: eight used a managed care model based on capitation or case rate setting; two were performance-based; and one contained a case rate and a performance contract. While the precise financial incentives and penalties differed across these state innovations, they all shifted financial risk to the service provider by penalizing agencies that did not meet contractual expectations and had poor rates of achievement of various outcomes. Additionally, each waiver sought to increase child welfare agencies' flexibility in serving children and families, often by allowing contractors to pool service-related funds to meet specific client or community needs (James Bell Associates, 2007).

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Due to federal waiver requirements, each market-based demonstration project was required to have an independent process, outcome, and cost evaluation. Table 1 summarizes the empirical results from the outcome evaluations that were conducted. Three state evaluations had not yet been completed, as their plans were still being implemented; two evaluations were not completed due to difficulties in implementing their plans. The six completed outcome evaluations sought to compare the permanency outcomes for children served by agencies under market-based (capitated, case rate, or performance-based) contracts as opposed to those served under fee-for-service contracts. Two state evaluations (Michigan and Ohio) identified insignificant experimental/control group differences in outcomes, including the rate of entry into foster care, achievement of permanency, and length of time in foster care. In contrast, evaluations in Indiana and North Carolina concluded that the use of market-based models containing case rates was associated with improvements in permanency outcomes such as increased reunification rates, decreased duration in foster care, and reduced rates of entry and reentry into foster care. The remaining two state programs showed mixed results, including an increased rate of adoption but no increase in reunification or foster care exit rates under a capitated managed care model (Maryland) and an increased rate of reunification in the first year of the evaluation but no improvements in reunification thereafter in a performance-based contracting environment (Connecticut). Thus, results from these six state evaluations provide mixed evidence concerning the relationship between market-based contracting and the achievement of various outcomes. 2.2. Child and family covariates of foster care outcomes Prior research has identified child-specific predictors of reunification. The probability of reunification with biological parents has been negatively associated with length of time in foster care as well as the number of placements children experience while in foster care (Children's Bureau, 2006; Courtney, 1994, 1995; Goerge, 1990; Davis, Table 1 Permanency outcomes of recent market-based child welfare initiatives Market model a

State (jurisdiction)

CAP/CR

California (Alameda and County Time series Los Angeles counties) Florida (statewide) County Time series Indiana (statewide) Child Experimental

CAP/CR CAP/CR CAP/CR CAP/CR

CAP/CR

CAP/CR

CAP/CR PBC PBC

CAP/CR, PBC

Unit of Research design analysis

Effects on permanency outcomes b Results pending.

Results pending The experimental group experienced an increased reunification rate and reduced TPR and adoption rates, as compared to the control group. Maryland (Baltimore) Child Experimental The experimental group experienced an equivalent exit rate from FC and an increased adoption rate, as compared to the control group. Michigan (four counties) Family Experimental The experimental group experienced an equivalent rate of entry into FC, duration in FC, FC placements, and achievement of permanency, as compared to the control group. North Carolina Child Passive survey The pilot group experienced a decreased rate of entry into FC, duration in FC, and rate of reentry into FC, and an increased exit rate from FC, as (19 counties) (administrative database) compared to the non-pilot group. Ohio (14 counties) County Non-equivalent The pilot group experienced equivalent reunification and adoption rates, comparison group kinship care placements, duration in FC, and placement stability, as compared to the non-pilot group. Washington (Clark and Child Experimental The evaluation was not completed due to implementation difficulties. Spokane counties) Colorado Child Experimental The evaluation was not completed due to implementation difficulties. (Arapahoe county) Connecticut Child Experimental The experimental group experienced an equivalent rate of change in (two service regions) custody, an increased rate of reunification in first year, an equivalent rate of reunification in second year, and reduced time at residential treatment centers, as compared to the control group. Iowa (one Child Experimental Results pending service region)

Source: James Bell Associates (2007) and publicly-available state evaluation reports. a CAP/CR = capitation or case rate model; PBC = performance-based contracting model; FC = foster care. b FC = Foster Care; TPR = Termination of Parental Rights.

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Landsverk, & Newton, 1997; Wulczyn, 2004). Additionally, African American children (Courtney, 1995; McMurtry & Lie, 1992; Wells & Guo, 1999) and children with health (Courtney, 1995; Jones, 1998; Wells & Guo, 1999) and mental health service needs (Chamberlain, Price, Reid, Landsverk, Fisher, & Stoolmiller, 2006; Landsverk, Davis, Ganger, Newton, & Johnson, 1996) have been found to be reunified at reduced rates. Studies have also identified an inverse relationship between child age and reunification, with infants particularly unlikely to be reunified (Courtney, 1994, 1995; Fraser, Walton, Lewis, Pecora, & Walton, 1996; Smith, 2003; Wells & Guo, 1999). Specific family and household factors have also been associated with the likelihood of reunification with a biological parent. The likelihood of reunification is increased with two-parent families and younger mothers (Davis et al., 1997), while mothers with substance abuse, mental health, and/or housing needs are less likely to be reunified with their children (Courtney, McMurtry, & Zinn, 2004; Fraser et al., 1996; Jones, 1998; Wulczyn, 2004). The likelihood of reunification with a biological parent has also been found to covary with the type of allegation of child maltreatment. In particular, chronic neglect has been associated with reduced rates of reunification (Courtney, McMurtry, & Zinn, 2004; Davis et al., 1997; Goerge, 1990). Research on the child-level predictors of adoption has tended to focus on child age and race. Many studies have identified an inverse relationship between child age and likelihood of adoption (Testa, 2004; Wulczyn, Barth, Yuan, Harden, & Landsverk, 2005), and research has found that African American children are less likely to be adopted than Caucasian children (Barth, Courtney, & Berry, 1994; Barth, Courtney, Berrick & Albert, 1994; Courtney & Wong, 1996). Also associated with a diminished likelihood of being adopted are being older at the time of entry into the foster care system, having multiple placements while in the foster care system, and coming from a poor family (Barth et al., 1994; Brooks, James, & Barth, 2002; Wind, Brooks, & Barth, 2006). There is also some evidence that the most damaged and traumatized children—those who show signs of developmental, behavioral, or emotional problems—are less likely to be adopted than others in placement (Barth et al., 1994; Brooks, James, & Barth, 2002; Wind, Brooks, & Barth, 2006). Kinship care occupies a gray area in research on permanency. Numerous studies have demonstrated that relative foster placements are often quite stable over time (Berrick, 1998; Cuddeback, 2004; Goerge, 1990; Testa, 2001), yet research has also found that children placed with kin are less likely to be reunified or adopted (Barth et al., 1994; Berrick, 1998; Chamberlain et al., 2006; Courtney, 1994; Cuddeback, 2004; Davis, Landsverk, & Newton, 1997; Smith, 2003). The increased use of kinship foster care (Geen, 2003; Grogan-Kaylor, 2000), however, suggests that attention should be paid to identifying its correlates. Studies have found that young (Leslie, Landsverk, Horton, Ganger, & Newton, 2000), African American (Berrick, Barth, & Needell, 1994; Cuddeback, 2004; Grogan-Kaylor, 2000; Iglehart, 2004) children who have been placed in foster care due to neglect (Geen & Berrick, 2002; GroganKaylor, 2000; Leslie et al., 2000) are more likely to be placed with kin than in non-kin foster homes. Additionally, Grogan-Kaylor (2000) determined that children with health problems and those from poor households were less likely to enter kin placements, whereas children from female-headed households were more likely to be placed in these arrangements. 2.3. Worker and service covariates of foster care outcomes Worker turnover and caseload size have been hypothesized to negatively affect the movement of foster children out of care by reducing service contacts, continuity, and parent engagement (Children's Bureau, 2004; Goerge, Wulczyn, & Fanshel, 1994). Empirical tests of these hypotheses, however, have been rare. Goerge (1994) and Ryan, Garnier, Zyphur, and Zhai (2006) found that the likelihood of reunification was negatively associated with the number of caseworkers serving a case. Festinger (1996) and Ryan et al. (2006) found that children served by caseworkers with MSW degrees were no more likely to be reunified than those served by workers with only a bachelor's degree. Perry (2006) failed to identify differences across 20 performance measures for child welfare workers holding the MSW degree and those who did not. And Ryan et al. (2006) found no relationship between the probability of reunification and the match between the caseworker's and foster child's race/ethnicity. Supervising visits between foster children and caregivers, locating and connecting caregivers with drug treatment and other specialized services in the community, and providing parent training are core services performed by child welfare workers. The common belief that parent engagement and visitation are essential precursors of reunification (Children's Bureau, 2004; Dawson & Berry, 2002) is supported by research. First discovered by Fanshel and Shinn (1978) and corroborated by others (Davis, Landsverk, Newton, & Ganger, 1996; Farmer, 1996), researchers have

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identified a positive link between visitation and reunification. In a review of eight studies, Thomlinson (n.d.) concluded that the amount of parent–child visitation was positively related to the likelihood of reunification. The probability of reunification has also been positively associated with parental completion of court-ordered substance abuse treatment (Green, Rockhill, & Furrer, 2007; Gregoire & Schultz, 2001; Miller, Fisher, Fetrow, & Jordan, 2006; Smith, 2003; Smith, Johnson, Pears, Fisher, & DeGarmo, 2007) and parent skills training (Fisher, Burraston, & Pears, 2005; Fisher & Chamberlain, 2000; Fraser et al., 1996; Miller et al., 2006). 2.4. Implications of the extant literature for the current study Despite these research advances, important aspects of the relationship between market-based models and foster care outcomes remain unexplored. Because of design limitations, the outcome evaluations from the Title IV-E waivers (James Bell Associates, 2007) could not compare the relative influence of financial contracting mechanisms with other child, family, caseworker, and service covariates on the achievement of various placement outcomes. Additionally, much of the research on the outcomes of foster care has been concerned with reunification, with less attention paid to the correlates of adoption and placement in kinship care arrangements; even less is known about children in marketbased environments who do not reach permanency within appropriate timeframes. 3. Research questions The present study examined the influence of a specific market-based model on the outcomes of foster children and families, defined as reunification with a biological parent, placement with kin, termination of parental rights (TPR), or adoption. Two research questions organized the study: Do children served under a market-based, performancedriven model achieve different permanency outcomes than children served under a traditional fee-for-service model?; and Controlling for the financial model used, what other factors are associated with children reaching different outcomes? The study examined these questions with data from an evaluation of a performance-based, managed care contracting initiative in the Wayne County (Detroit), Michigan foster care system (Meezan & McBeath, 2003)1 . These data allowed for the estimation of the relative influence of the market-based environment, child and familyrelated factors, caseworker characteristics, and service provision on the placement outcomes that foster children experienced. 4. Methods This longitudinal, quantitative study examined the final dispositions of a sample of 243 foster children and families that were served by nonprofit child welfare agencies in Wayne County, Michigan from 2001 to 2004. These agencies contracted with Michigan's public child welfare agency—then known as the Family Independence Agency (FIA)—to provide foster care services under one of two payment mechanisms: a fee-for-service system that reimbursed agencies for their case-related expenses on a per child, per-diem basis; or a performance-based, managed care system that contained a lower per-diem rate, an initial lump sum payment to agencies for the provision of services, and financial bonuses for the movement of foster children into permanent placements and the sustainment of these placements (the “pilot” initiative). The fiscal structure of the pilot reimbursement system is compared with the non-pilot reimbursement structure in Table 2. 4.1. Research design This study took advantage of the conditions for a natural experiment in order to isolate the independent effect of the pilot initiative from other covariates of placement outcomes. Nonprofit agencies, which provide care for approximately 1

While the initiative did not contain some common managed care characteristics such as capitation or uniform case management services, it was considered by both the public child welfare agency and the nonprofit agencies to be a managed care initiative. Official documents described the initiative as a managed care system (Family Independence Agency, 2000), and administrators from agencies with performance-based, managed care contracts made public presentations in which they referred to the initiative as a managed care system.

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Table 2 Per child reimbursement structure of the Wayne County foster care permanency pilot initiative

Per-diem rate Payment upon intake into pilot Performance incentives Achievement of performance standard (either the child's return home or to a relative, or achievement of legal guardianship or independent living in 290 days; or achievement of termination of parental rights in 515 days) Child at home six months after initial discharge Child at home 12 months after initial discharge Adoption placement made within seven months of termination of parental rights

Non-pilot ($)

Pilot initiative ($)

18 – 34 0

13.20 2210

0

1900

0 0 0

1290 1600 1290

85% of the foster children and families in Wayne County, receive all of their foster care cases through the Family Assignment System (FAS). The FAS requires children entering foster care for the first time to be assigned to the next agency in the alphabetical queue of service providers. If an agency is at full capacity, the next agency in the queue is contacted, and if a space is available the child is placed with that agency. As a result, foster children in Wayne County are assigned to nonprofit service providers on a rotating basis that is unrelated to case characteristics. Due to this assignment mechanism, random assignment equivalence was initially presumed to exist between children and families in pilot and non-pilot agencies. This client-level equivalence between children and families served by the two reimbursement models has been established. As reported by Meezan and McBeath (2003) and as can be seen in the middle columns of Table 3, the pilot and non-pilot groups are indistinguishable on all child characteristics but one: children from pilot agencies were, on average, older than children from non-pilot agencies (6.74 versus 5.22 years; F = 5.39; df = (1, 242); p = 0.02). There were significant group differences for only two characteristics pertaining to the primary caregivers of sample children: a smaller proportion of caregivers of children from pilot agencies had been previously investigated by CPS for child maltreatment than those from non-pilot agencies (47% versus 63%, respectively) (χ2 = 4.50, df = 1, p = 0.03); and a greater proportion of caregivers of children from pilot agencies led female-headed households than those from nonpilot agencies (69% versus 53%, respectively) (χ2 = 5.18, df = 1, p = 0.03). The pilot and non-pilot groups were comparable on all measures pertaining to the formal allegation of maltreatment, measures describing other conditions in the biological household (e.g. presence of drug abuse, inadequate housing, domestic violence), and most measures capturing worker characteristics. Thus, the results presented in this study were derived from the equivalent of a randomized, post-test only, control group design. 4.2. Sampling method In order to examine the placement experiences of foster children, 243 foster children served by six pilot agencies (n = 175) and three non-pilot agencies (n = 68) were selected for inclusion in the sample between May and October of 2001. Children was admitted to the study if they were a resident of Wayne County; under the age of 13 or part of a sibling group in which at least one child was under the age of 13 (FIA mandated that only children under the age of 13, or those whose siblings were under this age, were eligible for pilot reimbursement payments); assigned to the agency through the FAS; ordered into care at the preliminary court hearing; and reentering foster care after at least 365 days had passed since the last non-relative out-of-home placement. If a child was reentering foster care in less than 365 days, then he/she was assigned to the agency that had prior supervisory responsibility. In cases where two or more children from a sibling group were eligible for the study, only two siblings were included in the sample. If the sibling group consisted of two children, both children were admitted to the sample. Where the sibling group consisted of more than two children, two children were randomly selected for study. 4.3. Data collection Information pertaining to the characteristics of foster children and their primary caregivers was collected once, 30 days after the child's entry into foster care. Information concerning the whereabouts of the children, the services

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provided to them and their families, and the characteristics of agency caseworkers serving sample children and families was collected at 30 days and then every 90 days thereafter, up to a total of 930 days in foster care. Data were gathered through quarterly reviews of case files, which contained reports from CPS, FIA-required assessments and service plans, and regularly updated case notes. Data collection stopped either at 930 days or when the court terminated FIA's supervision of the family. 4.4. Measures 4.4.1. Dependent variables Four dichotomous, mutually-exclusive measures operationalized the final disposition that each foster child experienced by the end of the study: reunification referred to whether the child had been returned to his or her biological parent(s); kinship care pertained to whether the child had been placed with a relative caregiver; termination of parental rights (TPR) referred to whether the child's biological parents had their parental rights terminated but the child had not yet been placed in an adoptive home; and adoption referred to whether the child had either had his or her adoption finalized or had been placed in an adoptive home and was awaiting adoption finalization. In addition, analyses were conducted on the group of children who remained in care at the end of the study without reaching any of these statuses. 4.4.2. Independent variables A number of measures were identified as potential correlates of these final dispositions. The measure operationalizing the influence of the market contracting environment was whether or not the foster child was served by an agency operating under a performance-based, managed care contract (pilot agency) or by an agency operating under a fee-for-service contract (non-pilot agency). Four measures related to the characteristics of the foster child. Time in care was measured by the number of days the child remained in foster care as of the 930th and final day of data collection; race was measured by a dichotomous variable indicating whether the child was African American or Caucasian (no other races or ethnicities were present in the sample); sex was coded by a binary variable indicating whether the child was male or female; and age was measured in years. Three measures related to the characteristics of the primary caregiver of the child. A binary variable indicated whether the primary caregiver had previously been investigated by CPS for suspected child maltreatment; age was measured in years; and family structure was captured by a dichotomous variable indicating whether or not the primary caregiver led a female-headed household. Two additional measures concerned the strengths and needs of foster children and their primary caregivers. These measures drew from a nine-item assessment of the child's strengths and needs and a 13-item assessment of the primary caregiver's strengths and needs that were completed within 30 days of the child's entry into care by agency caseworkers using FIA-developed forms. Items in the child assessment pertained to emotional behavior, physical health, substance use, family relationships, and non-family social relationships; the primary caregiver assessment concerned parenting skills, social support, domestic relationships, housing, and physical health. Analyses suggested that these measures of strengths and needs had acceptable psychometric properties: exploratory factor analyses (varimax rotation) of the individual items in each measure resulted in single factor solutions, suggesting that it was appropriate to sum the items into a summary measure. Additionally, the Cronbach's alpha associated with the measures of child and primary caregiver needs and strengths were 0.75 and 0.79 respectively, suggesting that they had acceptable internal consistency (Meezan & McBeath, 2003). A set of dichotomous measures identified the formal allegation leading to the child's placement in foster care: whether neglect was the sole reason for removal of the child; whether the child had been abandoned by his or her biological parents; whether physical abuse was the sole reason for removal of the child; whether neglect and physical abuse were the reasons for removal of the child; whether sexual abuse was the sole reason for removal of the child; whether neglect as well as emotional and physical abuse were the reasons for removal of the child; whether incarceration of parents or child-related alcohol/drug abuse or behavior problems led to the removal of the child; and whether none of these factors led to the removal of the child. A set of dichotomous measures captured whether specific conditions were present in the biological household, including drug abuse, inadequate housing, domestic violence, failure to protect children from maltreatment, and alcohol abuse. These measures were not mutually exclusive, since CPS or agency caseworkers identified the presence or absence of each of these conditions at the point of the child's removal from the caregiver's household.

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Table 3 Sample characteristics Full sample (n = 243) %

Pilot (n = 175)

Mean

%

(S.D.) Permanency outcomes Reunification Kinship care TPR Adoption None

33 15 21 24 8

Child characteristics Days the child spent in care Child is African American Child is male Child age

Primary caregiver characteristics Caregiver had been previously investigated by CPS for child maltreatment Caregiver age Female-headed household Caregiver needs and strengths

(n = 68) Mean

28 18 19 22 8

79 51

6.736 (4.785) 0.085 (4.006)

34.085 (9.535) 64

708.029 (246.542) 84 53

47

5.225 (3.781) −0.209 (4.556)

63 33.963 (9.865)

69 0.139 (6.620)

pa

6.86 5.97 0.92 10.45 0.13

⁎⁎ b ⁎ ns ⁎⁎ ns

0.60

ns

1.12 0.09 5.39

ns ns ⁎

0.18

ns

4.50

⁎

0.08

ns

5.18 0.21

⁎ ns

(S.D.)

661.806 (297.396)

6.318 (4.572) 0.000 (4.165)

χ 2 or F

Mean

46 6 25 4 9

78 51

52

%

(S.D.)

674.741 (284.347)

Child needs and strengths

Non-pilot

34.374 (8.769) 53

0.006 (6.944)

0.449 (5.835)

Formal allegation of child maltreatment None Neglect Abandonment Physical abuse Neglect and physical abuse Sexual abuse Neglect and emotional and physical abuse Other

6 54 13 9 7 4 4 3

6 56 13 10 6 5 3 2

7 49 13 7 9 3 6 6

5.19

ns

Conditions in the biological household Drug abuse in the household Inadequate housing Domestic violence Failure to protect Alcohol abuse in the household

37 35 11 10 8

40 37 9 9 7

28 28 16 12 10

3.18 1.91 2.91 0.36 0.51

ns ns ns ns ns

2.75

ns

0.11

ns

0.54

ns

2.77

ns

Caseworker characteristics Number of caseworkers over child's stay

2.794 (1.384) 17.927 (24.256) 22.371 (4.656)

Caseworkers' months of agency experience Caseworkers' caseload % of child's stay where caseworker/child race matched

49

2.909 (1.483) 16.633 (16.942) 22.135 (4.477) 52

2.500 (1.044) 21.256 (36.933) 22.978 (5.073) 43

(continued on next page)

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Table 3 (continued ) Full sample

Pilot

Non-pilot

(n = 243)

(n = 175)

(n = 68)

%

Mean

%

(S.D.) Caseworker characteristics % of child's stay where caseworker had more than a BA/BS degree Services In-agency, non-therapeutic service contacts In-agency, therapeutic service contacts Phone calls Referrals for community-based services Community-based services a b

10

Mean

8

117.963 (87.835) 9.033 (17.803) 45.457 (50.641) 17.483 (13.853) 9.223 (7.578)

%

(S.D.)

pa

4.47

⁎

16.79

⁎⁎⁎

19.00

⁎⁎⁎

2.99

ns

0.05

ns

4.55

⁎

Mean (S.D.)

14

106.086 (88.869) 5.211 (11.556) 41.549 (40.992) 17.503 (14.426) 8.857 (7.951)

χ 2 or F

148.529 (77.711) 18.868 (25.724) 55.515 (68.967) 17.433 (12.335) 10.179 (6.462)

Pilot/non-pilot comparisons made by ANOVA, Kruskal–Wallis, or cross-tabulations (depending on measurement level and normality considerations). ns = (p N .05); ⁎ = (p b .05), ⁎⁎ = (p b .01), ⁎⁎⁎ = (p b 0.001).

Other measures pertained to the characteristics of the caseworkers serving foster children and families. A critical measure was the number of caseworkers that served the foster child over his or her stay in care. Given the possibility of multiple caseworkers serving a foster child, other measures included the average number of months of experience that each foster child's caseworker(s) had within the agency; and the average size of the caseload that the foster child's caseworker(s) was responsible for (measured in number of family cases as opposed to individuals). The similarity of the child's and the caseworker's racial background was captured by identifying the percentage of a child's stay in care in which both the foster child and the caseworker(s) were either Caucasian or African American. Caseworkers' educational level was measured by calculating the percentage of a child's stay in care in which the foster child's caseworker(s) had more than a baccalaureate degree. Finally, five measures operationalized the amount of services that agencies provided each foster child and family while in care. These included the number of in-agency, non-therapeutic service contacts provided to foster children and their families, which included home visits and case management-related activities; the number of in-agency, therapeutic service contacts provided to foster children by counselors, psychiatrists, and/or psychologists; the number of phone calls that agency caseworkers made to FIA and other collateral agencies; the number of referrals for out-ofagency services made on behalf of foster children and their families; and the number of different out-of-agency services that foster children and their families received. 4.5. Analytic methods Two sets of quantitative analyses were conducted. Univariate and bivariate analyses were completed to describe sample children and families, and to identify statistically significant differences between children who experienced different final dispositions. Initially, a multinomial logistic regression modeling approach (Long, 1997) was considered for conducting the multivariate analyses, using a five-point nominal dependent variable whose categories included reunification, kinship care, TPR, adoption, and no permanent placement achieved. This approach was discarded, however, in favor of separate multivariate logistic regression analyses in order to more clearly identify the contribution of various predictors to each type of outcome and to highlight the differences in the predictors of the various final dispositions. Given a maximum sample size of 243 foster children, adequate statistical power could not be maintained if all covariates of service provision were included in multivariate statistical models. Therefore, to preserve statistical power and identify a consistent set of independent variables across all dependent variables, covariates that were significantly related at the p b 0.05 level with at least two final dispositions in bivariate logistic regression analyses were retained for

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inclusion in multivariate analyses. This procedure thus excluded those covariates that proved unrelated in bivariate analyses to all or most final dispositions under examination.2 Due to the sampling frame used, where up to two siblings could be admitted into the study, the clustering of children within families and within agencies was of concern. Without correcting for the clustered or nested nature of the sample, estimates of variances would be artificially reduced, thus increasing the likelihood that coefficient estimates would be significant for no other reason than the non-independence of sample units (Greene, 1997; Guo, 2005; Guo & Wells, 2003; Wooldridge, 2002). To correct for this nesting of children within families and within agencies, clustered standard errors (STATA Corporation, 2003) were used in all logistic regression analyses. Finally, in order to allow for the comparison of effect sizes, the coefficients for the multivariate logistic regression analyses were reported as relative odds ratios. These odds ratios, which were calculated by exponentiating the logistic regression coefficients, identify the expected relative change in the predicted odds of achievement of the final disposition under examination associated with a one-unit change in the independent variable. 5. Results 5.1. Descriptive results of the full sample and the pilot and non-pilot groups At the end of the study, 80 children (33%) were reunified with their biological parents, 36 children (15%) were placed with relatives, 51 children (21%) had biological parents whose parental rights had been terminated but had not yet been placed in an adoptive home, and 57 children (24%) either had their adoption finalized or had been placed in an adoptive home and were awaiting finalization. Only nineteen of the children (8%) had achieved no permanent placement by the end of the study period. As seen in the first data column of Table 3, while 108 children (44%) remained in care through the entire 930 days of data collection, children spent an average of 675 days in care. Since the study drew children primarily from Detroit, where large numbers of African Americans reside, it is not surprising that over three quarters of the sample (n = 193) was African American. Half of sample children (n = 125) were male, and children were six years old on average upon entering foster care. The average standardized score for the caseworker-completed assessment of child needs and strengths was zero, suggesting that children demonstrated no more needs than strengths in terms of their social, emotional, and physical development. Roughly half of primary caregivers (n = 112) had been previously investigated by CPS for child maltreatment. Primary caregivers were, on average, 34 years old at the point of their children's entry into care, and roughly two-thirds of them (n = 146) led female-headed households. The average standardized score for the caseworker-completed assessment of primary caregiver needs and strengths was 0.14, which implies that primary caregivers demonstrated slightly more strengths than needs across dimensions including parenting skill, social support, and emotional stability. Nearly all children were removed from their biological households because of a formal allegation of neglect, physical abuse, abandonment, sexual abuse, or some combination of these types of maltreatment. Fifteen children (6%) were placed in foster care in the absence of a formal allegation of child maltreatment. The legal justification for the removal of these children is unclear. Chronic neglect (unaccompanied by any other form of child maltreatment) was by far the most prominent reason for removal, with over half of the sample (n = 131) being removed for this reason. Roughly an eighth of the sample (n = 31) had been abandoned. Less than a tenth of the sample had been physically abused (n=22), neglected and physically abused (n = 16), sexually abused (n = 10), or neglected as well as emotionally and physically abused (n = 9). Finally, eight children (3%) were removed for other reasons, including incarceration of their parents or child-related substance abuse or behavior problems. Over a third of the sample came from households in which drug abuse (n = 89) or inadequate housing (n = 84) had been identified by CPS and/or agency caseworkers. Roughly one tenth of sample children came from households in which domestic violence (n = 26) had been identified, or in which a household member was judged to have failed to protect a child (n = 24). Finally, 20 children (8%) had inhabited a household in which alcohol abuse had been identified. 2

These excluded variables included: child race and gender; primary caregiver family structure and prior involvement with CPS; some formal allegations of child maltreatment, including sexual abuse, neglect, and combinations of neglect and different types of abuse; some conditions in the biological household, including alcohol abuse and failure to protect children from maltreatment; caseworker experience, caseload, race, and educational level; and all variables pertaining to the services provided to foster children and their families.

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Sample children and families were served by an average of three caseworkers while in care. These caseworkers had, on average, 18 months of experience and caseloads of about 22 families. Sample children were served by raciallysimilar caseworkers for roughly half their time in care, and were served by caseworkers with an advanced degree for about one tenth of their time in care. Finally, children and families received an average of 118 non-therapeutic service contacts and nine in-agency therapeutic service contacts by agency personnel while in care. Caseworkers made an average of 46 service-related phone calls to collateral agencies on behalf of children and families. An average of 18 referrals for out-of-agency services were made for each case, and an average of nine completed service referrals were achieved while children were in care. The middle and right-hand data columns of Table 3 display descriptive statistics for the pilot and non-pilot groups. Proportionally fewer pilot children than non-pilot children were reunified (28% versus 46%, respectively) (χ2 = 6.860, df = 1, p = 0.009). In contrast, proportionally more pilot children than non-pilot children were placed with kin (18% versus 6%, respectively) (χ2 = 5.969, df = 1, p = 0.015) and adopted (22% versus 4%, respectively) (χ2 = 10.453, df = 1, p = 0.001). There were no statistically significant differences, however, in the proportions of pilot and non-pilot children who experienced TPR (19% versus 25%, respectively) (χ2 = 0.917, df = 1, p = 0.338) and who did not experience any formal disposition by the end of the study (8% versus 9%, respectively) (χ2 = 0.132, df = 1, p = 0.716). There were no significant differences in the characteristics of children or primary caregivers beyond those already mentioned. There were, however, some group-based differences in the caseworkers serving foster children and families and the services they received. Significantly more non-pilot than pilot children and families were served by bettereducated caseworkers for a greater proportion of their time in care (14% versus 8%, respectively) (F(4,237) = 4.47, p = 0.039). Additionally, there were significant differences in the numbers of four types of services provided to pilot and non-pilot children and families: while in care, non-pilot children and families received significantly more nontherapeutic service contacts (149 versus 107; χ2 = 16.79; df = 1; p = 0.0001); more in-agency therapeutic service contacts (19 versus 5; χ2 = 19.00; df = 1; p = 0.0001); more phone calls to collateral agencies (56 versus 42; χ2=2.99; df=1; p=0.08); and more completed referrals for out-of-agency service (10 versus 9; χ2 = 4.55; df = 1; p = 0.03) than children and families served by pilot agencies. Thus, children and families from non-pilot agencies received significantly more service contacts than did pilot children and families (for further description and analysis of these service differences, see McBeath, 2006; McBeath & Meezan, in press). 5.2. Group-based differences by type of final disposition As shown in Table 4, children who experienced different final dispositions differed significantly along institutional, child, primary caregiver, caseworker, and service-related dimensions. Concerning agency affiliation, proportionally more pilot children were placed with relatives or were adopted whereas a smaller proportion of pilot children experienced TPR or were reunified (χ2 = 13.616, df = 1, p = 0.009). While 72% of the children in the study were served by pilot agencies, more than four-fifths of the children who were in kinship care or adoptive homes at the end of the study (89% and 82% respectively) were placed from pilot agencies; in contrast, fewer than two-thirds of those who were reunified with their biological parents or had their parental rights terminated (61% and 67% respectively) were served by pilot agencies. In terms of child characteristics, children who experienced TPR spent, on average, more days in care (M = 872) than children who experienced any other final disposition; in contrast, children who were reunified had the shortest average time in care (M = 496) (F(4,238) = 21.430, p = 0.000). Children who were placed with kin at the close of the study tended to be older than children in any other disposition group, with an average age of nearly 10 years; adopted children and children who experienced TPR had an average age of four and five years, respectively (F(4,237) = 14.480, p = 0.000). Children who remained in foster care without a disposition, who were in relative care arrangements, and who experienced TPR exhibited fewer strengths than needs; in contrast, children who were reunified or adopted by the close of the study exhibited more strengths than needs (F(4, 230) = 2.491, p = 0.044). Group-based differences existed for three measures related to the primary caregivers. Proportionally more children who experienced no final disposition (76%) or were in adoptive homes (67%) had primary caregivers who had been previously investigated for suspected child maltreatment (χ2 = 11.316, df = 4, p = 0.023). Children placed with relatives at the end of the study had, on average, the oldest parents or primary caregivers (M = 38), whereas children who experienced TPR had the youngest (M = 30) (F(4,214) = 3.210, p = 0.014). Finally, the primary caregivers of reunified

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Table 4 Group-based differences by type of final disposition Reunification

Market institutions Child is served by a pilot agency

TPR

Adoption

None

(n = 80)

(n = 36)

(n = 51)

(n = 57)

(n = 19)

% Mean

% Mean

% Mean

% Mean

% Mean

(S.D.)

(S.D.)

(S.D.)

(S.D.)

(S.D.)

61

Child characteristics Days the child spent in care Child is African American Child is male Child age

Kinship care

89

496.225 (279.734) 79 53

711.861 (291.326) 83 47

6.591 (4.247) 0.921 (4.480)

Child needs and strengths

67

Primary caregiver characteristics Caregiver had been previously investigated by CPS 44 for child maltreatment Caregiver age 34.266 (9.703) Female-headed household 57 Caregiver needs and strengths 3.183 (5.445)

82

872.039 (149.213) 78 61

9.904 (4.761) − 1.027 (5.308)

48

75 47 4.699 (3.198) − 0.287 (3.437)

45 37.604 (12.096)

55

4.227 (3.909) 0.201 (2.904)

67 30.348 (6.790)

77 − 0.122 (5.874)

851.421 21.43 (209.458) 89 2.118 42 3.116 9.007 14.48 (5.167) − 1.754 2.49 (4.480)

64 − 1.634 (6.870)

36.515 (11.995) 78

− 2.358 (7.407)

⁎⁎⁎ ns ns ⁎⁎⁎ ⁎

11.316 ⁎

76 33.570 (7.102)

pa

13.616 ⁎⁎ b

68

666.421 (243.847)

χ 2 or F

− 2.229 (5.629)

3.21

⁎

8.031 7.97

ns ⁎⁎⁎

Formal allegation of child maltreatment None Neglect Abandonment Physical abuse Neglect and physical abuse Sexual abuse Neglect and emotional and physical abuse Other

6 48 8 19 8 0 10 1

6 50 14 8 8 8 0 6

2 65 20 4 6 2 0 2

12 54 11 2 5 7 2 7

0 58 21 5 5 11 0 0

53.358 ⁎⁎

Conditions in the biological household Drug abuse in the household Inadequate housing Domestic violence Failure to protect Alcohol abuse in the household

22 29 15 13 5

31 33 14 6 3

51 55 10 4 8

56 23 5 12 16

16 42 5 16 11

25.725 14.319 4.427 4.573 6.895

⁎⁎⁎ ⁎⁎ ns ns ns

8.71

⁎⁎⁎

0.51

ns

1.72

ns

Caseworker characteristics Number of caseworkers over child's stay

2.175 (1.123) 18.870 (30.061) 22.933 (4.732)

Caseworkers' months of agency experience Caseworkers' caseload % of child's stay where caseworker/child race matched % of child's stay where caseworker had more than a BA/BS degree Services In-agency, non-therapeutic service contacts

2.889 (1.260) 13.838 (10.487) 21.144 (5.258)

3.510 (1.302) 20.872 (32.991) 22.540 (4.702)

2.982 (1.564) 16.591 (13.587) 21.712 (4.204)

2.737 (1.240) 17.803 (8.052) 23.848 (3.860)

46

52

51

58

30

2.03

ns

6

6

14

6

32

7.44

⁎⁎⁎

3.53

⁎⁎

126.625 (88.012)

121.972 (111.278)

135.431 (61.163)

81.474 (80.783)

136.474 (95.644)

(continued on next page)

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Table 4 (continued )

Services In-agency, therapeutic service contacts Phone calls Referrals for community-based services Community-based services a b

Reunification

Kinship care

TPR

Adoption

None

(n = 80)

(n = 36)

(n = 51)

(n = 57)

(n = 19)

% Mean

% Mean

% Mean

% Mean

% Mean

(S.D.)

(S.D.)

(S.D.)

(S.D.)

(S.D.)

6.500 (11.793) 41.388 (53.095) 15.200 (10.719) 9.175 (6.372)

8.528 (14.653) 47.556 (37.544) 16.806 (15.207) 7.250 (5.704)

11.490 (23.209) 49.725 (36.450) 18.157 (10.898) 9.725 (7.408)

8.825 (17.512) 34.193 (31.628) 20.036 (18.998) 9.393 (10.149)

14.684 (26.516) 80.947 (103.427) 19.053 (11.607) 11.316 (6.856)

χ 2 or F

pa

1.14

ns

3.4

⁎⁎

1.13

ns

1.04

ns

Group comparisons made by ANOVA, Kruskal–Wallis, or cross-tabulations (depending on measurement level and normality considerations). ns = (p N .05); ⁎ = (p b .05), ⁎⁎ = (p b .01), ⁎⁎⁎ = (p b 0.001).

children exhibited greater strengths than needs; the primary caregivers of children in other dispositions were assessed as having more needs than strengths (F(4, 218) = 7.972, p = 0.000). There were also significant differences regarding the type of child maltreatment and the household conditions experienced by different groups of foster children. Eighty five percent of the children who experienced TPR had been either neglected (65%) or abandoned (20%). In contrast, less than half of the children who had been reunified had been neglected (45%), although 37% had suffered physical abuse, either alone (19%) or in combination with neglect (8%) or neglect and emotional abuse (10%) (χ2 = 53.358, df = 28, p = 0.003). In terms of other conditions in the biological household, over half of adopted children (56%; n = 32) and children who experienced TPR (51%; n = 26) came from households in which drug abuse had been identified, compared to fewer than one third of the children who experienced no final disposition (16%; n = 3), were returned to their biological parents (22%; n = 18), or were returned to relatives (31%; n = 11) (χ2 = 25.725, df = 4, p = 0.000). Finally, while over half of children who experienced TPR (55%; n = 28) came from households deemed materially inadequate by CPS and/or agency caseworkers, no more than a third of other groups of children came from families whose household conditions were considered inadequate (χ2 = 14.319, df = 4, p = 0.006). In terms of caseworker characteristics, children who experienced TPR were served by more caseworkers (M = 3.5), on average, than children experiencing other final dispositions; in contrast, children who were reunified interacted with the fewest caseworkers (M = 2.2) (F(4, 238) = 8.710, p = 0.000). Additionally, children who experienced no final disposition and children who experienced TPR spent a greater proportion of their time in care being served by master'sdegreed caseworkers than other children (32% and 14%, respectively, versus 6% for each of the other final dispositions) (F(4, 238) = 7.440, p = 0.000). Finally, children who experienced different final dispositions received different amounts of two types of in-agency services. Children who experienced no final disposition received the most non-therapeutic service contacts (M = 136), whereas adopted children received the fewest (M = 82) (F(4, 238) = 3.536, p = 0.003). Similarly, children who experienced no final disposition had the most case-related phone calls (M = 81) placed on their behalf while caseworkers made the fewest case-related phone calls (M = 34) on behalf of adopted children (F(4, 238) = 3.400, p = 0.009). 5.3. Multivariate results As seen in Table 5, children served by pilot agencies were 68% less likely than non-pilot children to be reunified with their biological parents, controlling for other covariates of reunification. In addition, an extra day in care was associated with less than a half percent decrease in the odds of reunification. And a one standard deviation increase in the assessment of children's and primary caregiver's strengths and needs (indicating more strengths) was related to a 15% and an 11% increase in the odds of reunification, respectively. No statistically significant relationship emerged between reunification and any variables pertaining to the allegation of child maltreatment, various conditions in the biological household, or caseworker characteristics.

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Table 5 Logistic regressions by final disposition Reunification Market institutions Child is served by a pilot agency

Child characteristics Days the child spent in care Child age Child needs and strengths

Primary caregiver characteristics Caregiver age

Kinship care

0.315 a (0.151)

⁎b

3.821 (1.755)

0.997 (0.001) 1.042 (0.049) 1.151 (0.056)

⁎⁎⁎

1.001 (0.001) 1.212 (0.115) 0.973 (0.050)

⁎⁎

⁎⁎

⁎

TPR

Adoption

0.516 (0.217)

1.743 (0.911)

1.004 (0.002) 0.866 (0.046) 0.904 (0.066)

0.999 (0.002) 0.780 (0.048) 0.970 (0.058)

⁎⁎

1.006 (0.030) 1.014 (0.043)

0.957 (0.019) 0.962 (0.051)

⁎

1.026 (0.039) 0.980 (0.057)

0.301 (0.217) 1.229 (0.684)

1.071 (1.447) 0.755 (0.575)

5.153 (3.090) 2.241 (3.790)

⁎⁎

0.950 (0.485) 0.171 (0.206)

Other conditions in the biological household Drug abuse 0.570 (0.173) Inadequate housing 0.828 (0.314) Domestic violence 3.975 (5.208)

0.790 (0.634) 0.642 (0.369) 1.433 (0.781)

3.289 (1.737) 3.337 (1.620) 0.449 (0.206)

⁎

2.192 (1.190) 0.601 (0.297) 0.795 (0.724)

1.077 (0.324) − 78.613

1.088 (0.125) − 70.661

Caregiver needs and strengths

Formal allegation of child maltreatment Abandonment Physical abuse

Caseworker characteristics Number of caseworkers over child's stay (− 2 ln L) a b

0.986 (0.022) 1.111 (0.054)

1.037 (0.205) − 91.860

⁎

⁎

⁎⁎⁎

0.994 (0.269) − 74.277

N = 201. Results are logistic regression coefficients reported as odds ratios, with robust standard errors (clustered by agency) in parentheses. ⁎ = (p b .05), ⁎⁎ = (p b .01), ⁎⁎⁎ = (p b 0.001).

The odds of kinship placement were 3.8 times higher for children served by pilot agencies, controlling for child, primary caregiver, and caseworker factors. And an additional year in the child's age at entry into care was associated with a 21% increase in the odds of kinship placement by the end of the study. No other covariates in the model were statistically significant in predicting placement with relative caregivers. In contrast to reunification and kinship care, pilot or non-pilot status was not a significant covariate of either TPR or adoption. However, five other correlates of TPR were statistically significant. Controlling for all other covariates in the model, an additional year in the child's age at entry into care was associated with a 13% decrease in the odds of the child experiencing TPR. Similarly, an additional year in the primary caregiver's age at the time of the child's entry into care was associated with a four percent decrease in the likelihood that the child's disposition would be TPR. Abandoned children were 5.2 times more likely to experience TPR than children who had not been abandoned. Finally, children from both drug-abusing households and inadequate households were 3.3 times more likely to experience TPR by the close of the study than children from households in which these conditions were not present. Only one covariate was significant in predicting adoption. Controlling for pilot or non-pilot status as well as other child, primary caregiver, household, and caseworker characteristics, the odds of adoption were decreased by 22% for each year of the child's age at entry into care.

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Finally, two additional sets of multivariate analyses were conducted which are not reported in Table 5. The first sought to identify factors associated with the lack of achievement of a final disposition. None of the covariates included in logistic regression models was statistically significant (p b 0.05). The second set of analyses examined whether there were changes in regression coefficients if the variable pertaining to market institutions was omitted from the logistic regressions reported in Table 5. The direction, size, and statistical significance of the remaining coefficients remained largely unchanged, attesting to the stability of the models and the relative importance of the previously identified variables in predicting various foster care outcomes. 6. Discussion The appearance of managed care and performance-based contracting in state child welfare systems is a consequence of the increased attention that federal and state policymakers are paying to the performance of child welfare systems and their attendant costs. Despite the spread of market-based models into the child welfare sector, there have been few scientific studies testing their impact or effectiveness. Thus, at a time when many managed care demonstration projects have been or are being implemented, it is an open question as to how market-based models affect various outcomes for children in foster care. This study embedded a series of statistical analyses within a longitudinal natural experiment to isolate the effects of a performance-based, managed care contracting mechanism on foster care permanency outcomes. Initial analyses identified significant differences in the final dispositions experienced by foster children in the market-based environment as opposed to those served by child welfare agencies reimbursed through fee-for-service contracts. In particular, children in market-based environments were significantly less likely to be reunified and more likely to be placed in kinship foster homes and adopted, as compared with other children at the close of the study. Subsequent multivariate logistic regression analyses identified market-based disparities in reunification and kinship care but not TPR or adoption. 6.1. Limitations These results should be considered within the context of the limitations of the study. In particular, although the study's research design had random assignment equivalence, some threats to internal validity remained. First, because the small sample size necessitated the use of parsimonious regression models, the omission of variables in the final regression models might have biased the multivariate results. Second, because of the inability to collect outcome data prior to the beginning of the study, it is difficult to ascertain whether the differences in outcomes were the result of the financial model being used or were similar to the outcomes achieved by the agencies prior to the start of the study. In terms of external validity, this study evaluated the effects of performance-based, managed care contracting on foster children and families within only one county. The generalizability of these results therefore depends on the extent to which the Wayne County foster care pilot initiative is similar to other jurisdictions' market-based initiatives in terms of financial risk structure, caseworkers, and client population. 6.2. Implications for research, practice, and policy Despite these study limitations, the current research suggests a number of implications for child welfare research, practice, and policy. The rate of reunification identified for sample children (33%) was nearly identical to that of other studies (Courtney, 1994; Fraser et al., 1996). The number of adoptions that were completed within three years, however, was higher than might have been expected (Wulczyn, Harden, & Goerge, 1997), and the proportion of children still present in the foster care system after 930 days without a permanent placement was less than has been reported in other studies (Fanshel & Shinn, 1978; Wulczyn, Harden, & Goerge, 1997). Perhaps the mere presence of competition between two sets of agencies working under different market arrangements explains these findings. Future research should examine the impact of interagency competition on the achievement of outcomes. This study demonstrated that the pilot initiative may have affected some of the paths through which children exit care. It is plausible to hypothesize that some pilot agencies achieved performance bonuses by placing pilot children with kin rather than returning them to their biological parents because these placements were easier to achieve. That is,

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the market-based contracting mechanism may have changed the operational conception of permanency planning at pilot agencies by shifting attention away from reunification-related efforts to the search for relative placements. Future research might examine whether certain market-based models alter service providers' efforts with biological parents and whether caseworkers perceive kinship placement to be easier to achieve than reunification. It should be remembered that children and families who were successfully reunified in this study were those who entered the foster care system with more strengths than others in the study, a finding that accords with prior studies of foster care (Chamberlain et al., 2006; Courtney, 1995; Landsverk et al., 1996). The increased rate of kinship foster placements in this market-based contracting environment suggests that further research is necessary on the stability of kinship foster placements and the well-being of children placed with relatives in market-based child welfare initiatives. Given that kinship caregivers may receive fewer services and less financial support than non-relative caregivers (Cuddeback, 2004; Geen, 2003), it is important to understand how well children in these placements fare over long periods of time, the strains they cause on their kin caregivers, and the rewards derived by both parties in these placements. It is not clear why this specific performance-based, managed care contracting environment affected rates of reunification and kinship care but not TPR and adoption. Future research might examine the permanency-related decision calculus of child welfare caseworkers in market and non-market environments. It is possible that caseworkers at all study agencies engaged in a two-stage decision-making process, in which they quickly decided whether a particular foster child could be reunified or placed with a relative within the performance timeframes, and, if not, began to move towards adoption quickly. This possibility suggests a subtle but important change to the traditional model of permanency planning, in that kinship foster placement is considered at the same time rather than after reunification. While the multivariate analyses determined that the adoption process was not sensitive to the pilot contracting environment, differences in child and primary caregiver needs and strengths, or varying conditions in the biological household from which children were removed, the identification of an inverse relationship between child age and the likelihood of TPR and adoption is similar to that seen in prior research (Barth et al., 1994; Testa, 2004; Wulczyn et al., 2005). And the bivariate results concerning TPR and adoption also fit expectations: adoption was more likely to occur for children whose biological parents had been previously investigated by CPS; and TPR and adoption were more likely to occur for children with substance abusing parents and who were neglected, and less likely to occur for children who were physically abused (Barth et al., 1994; Brooks, James, & Barth, 2002; Wind, Brooks, & Barth, 2006). The potential for differentiation between pilot and non-pilot agencies in terms of achieving “deep end” outcomes (TPR, adoption) for children may have been suppressed by the presence of the court system. It may be that court officials, who did not differentiate between the market environments in which children were being served, continued to operate in their usual manner without an understanding of the potential impact of their actions on monetary reimbursements to pilot agencies. No empirical study has examined the role of court officials in either slowing or expediting the pace of proceedings for foster children in market-based environments. This gap in the literature is surprising given that the courts retain formal oversight of foster children and are often more careful monitors of nonprofit agencies' compliance with service and permanency plans than they are of public child welfare agencies (Ellett & Steib, 2005). The omission of court-related processes in this study and its multivariate models may have contributed omitted variable bias to the results. In addition, two findings from this study question the effectiveness of current front-line practices in foster care. First, the general insignificance of the five measures of service provision implies that child welfare caseworkers' efforts to implement visitation and service plans, and link children and families with in-and extra-agency services, had little direct effect on outcomes. Second, despite the emphasis in PL 105-89 and in state child welfare demonstrations on expediting permanency for foster children, this study found that a considerable number of children had not achieved permanency by the end of 930-day study period, and were therefore at risk of becoming “system orphans”. Of particular concern were the children who were not in a permanent placement (8%) or who experienced TPR but had not yet begun the adoption process (21%) by the end of the study. These figures imply that the lower number of children in this study who were drifting in foster care without permanent plans was more than offset by the number of children without firm plans for adoption even though their parental rights had been terminated. It is therefore an open question whether changes in permanency planning guidelines limiting the time caseworkers are able to work with families before beginning TPR proceedings have simply moved the problem of drifting children further down the permanency continuum.

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Studies have noted that children who languish in foster care or await adoptive homes are more likely to be older, from minority backgrounds, are part of sibling groups, have significant behavioral problems and other special needs, and/or have other factors that prevent their parental rights from being terminated (Barth et al., 1994; Brooks, James, & Barth, 2002; Wind, Brooks, & Barth, 2006). The results from this study support only some of these relationships. This study found that children who experienced TPR but were not yet adopted were younger, had parents who were younger, and had been abandoned. While contrary to previous research, these findings augur well for the future adoption of these children. This study also found that those awaiting adoption were more likely to have been removed from families with drug abuse problems and inadequate housing, which might suggest that these families had greater needs due to previous deprivation. Yet children's strengths and needs score was not predictive of their TPR or adoptive status, which might suggest that unknown factors were at work. More research is needed to examine whether PL 105-89 has led state child welfare systems to experience blockages to adoption created by hastened timelines to TPR. This study has two profound implications for child welfare policymakers. First, federal and state policymakers should ensure that child welfare systems preserve their commitment to parent–child reunification, particularly as they seek to manage financial risk by searching for least costly permanency alternatives. In the context of PL 105-89 as well as state demonstration projects, child welfare agencies are rewarded for expediting the achievement of any permanent placement. However, the cost of reaching different foster care outcomes may differ. In particular, reunification of high-need families may be disproportionately expensive for child welfare agencies as compared to the costs of kinship care, guardianship, or adoption. These higher costs associated with reunification often derive from the need for and provision of expensive in-agency and community-based services to parents, the coordination and monitoring of these services by caseworkers, and protracted work with the court system. In the context of these costs, moving towards reunification may be financially risky for child welfare agencies working in market-based systems, particularly if the odds of treatment failure are high and the likelihood of returning the child home is low. If agencies are allowed to choose which permanent placement is to be achieved, then high-risk parents may not receive the reunification-related opportunities and resources that they need. Alternatives to reunification may be less costly for child welfare agencies and systems, but may not be the best choice for children who remain attached to their biological parents. Finally, this study demonstrates the value of incorporating multivariate analyses within an experimental design in order to isolate the independent effect of a change in child welfare policy from contemporaneous factors. The strength of experimental designs is their ability to preserve internal validity through the creation of groups with comparable individual-level characteristics. Group-based differences may exist, however, at higher units of analysis, such as service provision to children and families and caseworker characteristics. Because these higher-order nonequivalencies may affect the permanency outcomes of the experimental and control groups, analytical strategies that do not specifically control for multi-level factors may produce biased results. For example, while bivariate analyses in this study identified a significant difference in the rates of adoption for pilot and non-pilot children, this marketbased disparity became insignificant once child, family, and caseworker factors were included in multivariate analyses. That is, the significant bivariate relationship between the market-based contracting environment and achievement of adoption was an artifact of omitted variable bias. By inference, it is possible that many of the outcome evaluation results from the state market-based demonstrations contain similarly biased results given these evaluations' reliance on group-based data. 6.3. Conclusions Neither this study nor previous research is able to suggest that market-based models are associated with uniform improvements in foster care outcomes. This study identified sizable market-based disparities in the rates of reunification (favoring non-market-based agencies) and kinship care (favoring market-based agencies) and equivalent rates of TPR and adoption. These results call into question the evidentiary basis for the diffusion of managed care and performance-based contracting in the child welfare sector. State child welfare systems should ensure that foster care placement decisions are influenced more by child and family conditions than by financial considerations. Managed care and performance-based contracts should include specific financial incentives for reunification and for reductions in foster care drift. In short, market-based mechanisms should provide incentives for child welfare agencies that attend to the very different processes through which foster children exit foster care.

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