Abstract: Risk, Race, and Community-Based Service Referrals in Los Angeles County, California (Society for Social Work and Research 27th Annual Conference - Social Work Science and Complex Problems: Battling Inequities + Building Solutions)

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Risk, Race, and Community-Based Service Referrals in Los Angeles County, California

Friday, January 13, 2023
Encanto B, 2nd Level (Sheraton Phoenix Downtown)
* noted as presenting author
Claire McNellan, MPH, Doctoral Student, University of North Carolina at Chapel Hill, Chapel Hill, NC
Lindsey Palmer, PhD, Postdoctoral Fellow, The Pennsylvania State University, PA
Emily Putnam-Hornstein, PhD, John A. Tate Distinguished Professor for Children in Need, University of North Carolina at Chapel Hill, Chapel Hill, NC
Jacquelyn McCroskey, PhD, Professor, University of Southern California, Los Angeles, CA
Background and Purpose: Child protection system (CPS) agencies often provide services to families through referrals to other providers, rather than directly. Yet, we know little about which families are referred to services because that information is generally recorded in non-CPS data systems. One area that has been under-explored relates to potential racial disparities in referrals to services that could protect against future CPS involvement. We use a unique source of linked administrative and community-based services data from Los Angeles, California to (1) assess community service patterns between risk categories as defined by our risk-stratification model, and (2) examine community service patterns within risk categories to assess differences by racial and ethnic groups.

Methods: This paper linked risk scores generated from a predictive risk model with LA county service referral records to examine the relationship between risk of future foster care placement and service referral receipt. The predictor variable, risk, was estimated using a predictive risk model developed from more than 300 data features and trained to classify risk of foster care placement within two years using records from 2016-2017 (N = 341,428). Records documenting referrals to services from contracted community providers in LA were extracted and linked to child-referral records using the client ID. Using the predicted probabilities calculated by the predictive risk model, we kept the highest risk score calculated for each child. A logistic regression was used to estimate the odds of receiving services referral by investigation disposition, focal child’s age, race and ethnicity, risk score, and race-by-risk interactions.

Results: Overall, following an investigation for alleged maltreatment in which the child was not removed, only 21.2% of families were referred to community-based services (N = 44,889). The median risk score of families referred to services (0.31) was slightly higher than the median risk score of those who were not referred to services (0.23). Results of the logistic regression indicated that, compared to White children, the unadjusted odds of receiving a referral were higher for Black (OR = 1.47, p < .01), and Hispanic (OR = 1.68, p <.01). After adjusting for risk, the interaction between risk and race, and other factors, the odds of receiving a referral were higher for Black (OR=1.43, p<.01) and Hispanic children (OR = 2.00, p < .01) compared to White children. There was evidence of a significant interaction between race and risk for both Black and Hispanic children.

Conclusions and Implications: Across all racial and ethnic subgroups, families with higher risk scores were more likely to receive referrals; however, even among families with the highest scores, most were not referred, suggesting opportunity to expand service connections. Some differences by race remain after accounting for risk score. Using predicted probabilities from our model, we found that racial disparities in community-service referrals were greater at low risk than at high risk. Across risk scores, Hispanic families were more likely to receive a service referral than any other group and this variation remains unexplained.