Structured Decision Making (SDM)

About This Program

Target Population: Families referred to and assessed by child protective service (CPS) agencies

For children/adolescents ages: 0 – 17

For parents/caregivers of children ages: 0 – 17

Program Overview

SDM is a comprehensive case management system for Child Protective Services (CPS). CPS workers employ objective assessment procedures at major case decision points from intake to reunification to improve child welfare decision-making. SDM targets agency services to children and families at high risk of future child welfare system involvement and helps ensure that service plans reflect the strengths and needs of families. When effectively implemented, it increases the consistency and validity of case decisions, reduces subsequent child maltreatment, and expedites permanency. The assessments from the model also provide data that help agency managers monitor, plan, and evaluate service delivery operations..

Program Goals

The primary goals of Structured Decision Making (SDM) are:

  • Reduce subsequent maltreatment
  • Reduce time to permanency
  • Increase the accuracy and consistency of decision making at critical points in child welfare casework

Essential Components

The essential components of Structured Decision Making (SDM) include:

  • The primary goal of the SDM case management system in CPS is to reduce the subsequent maltreatment of children in families where an abuse or neglect incident has occurred.
    • The underlying logic is that the best way to accomplish this goal is to accurately identify families at high risk for maltreatment, prioritize them for agency service intervention, and then effectively deliver services appropriate to their needs.
    • The following SDM assessments were designed to help workers make decisions necessary to accomplish these tasks. Use of the assessments can also help bring a greater degree of equity, reliability, and accuracy to case decisions. The model includes the following components:
      • Intake assessment: Helps intake or hotline workers make accurate, consistent decisions about which families need an in-person response from child protective services and how quickly that response should occur.
      • Safety Assessment: This helps workers identify the immediate protective service interventions (including child removal) required, if any, during a CPS investigation or case.
      • Research-Based Risk Assessment: This estimates the likelihood of subsequent system involvement and informs the decision to provide services and how often a worker should have contact with a family.
      • Objective Strengths and Needs Assessment: This helps workers identify and prioritize the specific service interventions needed to construct an effective treatment plan.
      • Periodic Reassessments of Safety, Risk, and Needs: These measure progress and help workers update the treatment plan and review readiness for case closure.
      • Reunification Assessment: This informs workers' decision to reunify the child with his/her family or to change the permanency-planning goal.
      • Service Levels (e.g., low, moderate, high, and intensive) Based on Results of the Risk Assessment: These guide the minimum contact standards a worker makes with the family. This practice ensures that staff time and attention are concentrated on those families at the highest levels of risk and need.
      • Efforts to Support Equity: These include participation of multiple stakeholders with an acute awareness of power, privilege, and disproportionality. Stakeholders hold this multicultural lens when doing the following throughout the SDM process:
        • Customizing items and definitions in the development phase
        • Testing for equity in risk validation studies in the research phase
        • Continuous quality improvement to evaluate consistent application of items across cultures
        • Supervision/coaching to increase awareness of application of items across cultures
        • Use of aggregate data cross-tabulated by race/ethnicity to examine patterns
        • Use of findings to focus efforts to increase equity in the postimplementation practice and evaluation phase.

Program Delivery

Child/Adolescent Services

Structured Decision Making (SDM) directly provides services to children/adolescents and addresses the following:

  • Experience with or exposure to abuse or neglect and family has an open child welfare services case

Parent/Caregiver Services

Structured Decision Making (SDM) directly provides services to parents/caregivers and addresses the following:

  • Their child experienced or was exposed to abuse or neglect and their family has an open child welfare services case

Recommended Intensity:

The number of face-to-face contacts between a family and the caseworker varies based on the risk level obtained from completing the risk assessment. The number of contacts increases with an increase of the family risk level. The goal of differential contact standards is to target limited resources to those families most at risk of future system involvement. For example, a very high-risk family will have four face-to-face contacts (at least two with the case manager) per month, while a moderate risk family will have two face-to-face contacts (at least one with the case manager) per month.

Recommended Duration:

Caseworkers employ assessments throughout the life of a CPS case, from intake to closure from foster care or in-home services.

Delivery Setting

This program is typically conducted in a(n):

  • Public Child Welfare Agency (Dept. of Social Services, etc.)

Homework

This program does not include a homework component.

Resources Needed to Run Program

The typical resources for implementing the program are:

Usually existing agency resources can be used. A management information systems component is strongly recommended.

Education and Training

Prerequisite/Minimum Provider Qualifications

Minimum qualifications for workers using the case management system are determined by the CPS agency.

Education and Training Resources

There is a manual that describes how to deliver this program, and there is training available for this program.

Training Contact:
Training is obtained:

Training is typically provided onsite, as either a training-for-trainers or direct training of workers and supervisors.

Number of days/hours:

2 to 4 days (depending on the number of assessments being trained)

Implementation Information

Pre-Implementation Materials

There are pre-implementation materials to measure organizational or provider readiness for Structured Decision Making (SDM) as listed below:

An organization is helped to fully understand the implications and process for adopting SDM. This includes, but is not limited to:

  • Understanding the objectives the organization wishes to achieve
  • Assisting in developing a logic model for the project
  • Reviewing the elements (i.e., implementation drivers) needed for success
  • Contributing to an informed decision on whether the organization is ready, and if not, what would help to prepare PowerPoint presentations are used in conversations with jurisdictions who are considering SDM, and throughout implementation to explain and continuously revisit implementation drivers.

Formal Support for Implementation

There is formal support available for implementation of Structured Decision Making (SDM) as listed below:

The program offers assistance to a jurisdiction interested in implementing SDM from pre-implementation through sustainability. Assistance with the following implementation related-issues can be provided:

  • Change management
  • Policy and procedure integration
  • Implementation planning
  • Helping to build organizational culture and climate that supports learning
  • Training
  • Coaching
  • Developing internal capacity for training and coaching
  • Data collection
  • Automation consultation
  • Quality improvement
  • Analytics
  • Evaluation

Fidelity Measures

There are fidelity measures for Structured Decision Making (SDM) as listed below:

Specific fidelity measures fall into these groups:

  • Completion rates
  • Accuracy of completion
  • Alignment of actions taken with actions recommended
  • Case reading
  • IRR testing
  • Surveys, focus groups, interviews, and/or observations with staff using SDM

Please note that SDM is typically taught within a family-centered, strengths-based, and safety-focused practice framework. Fidelity of these practice skills should also be evaluated, though this is not specifically part of SDM.

Implementation Guides or Manuals

There are implementation guides or manuals for Structured Decision Making (SDM) as listed below:

The implementation plan is customized for each site. Using the implementation drivers, combined with steps needed to customize the jurisdiction's SDM assessments and policies, a plan is customized to identify actions needed throughout pre-implementation, implementation and sustainability phases.

Research on How to Implement the Program

Research has not been conducted on how to implement Structured Decision Making (SDM).

Relevant Published, Peer-Reviewed Research

Child Welfare Outcomes: Safety and Permanency

A meta-analysis, see citation following, has been conducted on the Structured Decision Making (SDM), however, this article is not used for rating and therefore is not summarized:

  • van der Put, C. E., Assink, M., & van Solinge, N. F. B. (2017). Predicting child maltreatment: A meta-analysis of the predictive validity of risk assessment instruments. Child Abuse & Neglect, 73, 71–88. https://doi.org/10.1016/j.chiabu.2017.09.016

When more than 10 research articles have been published in peer-reviewed journals, the CEBC reviews all of the articles as part of the rating process and identifies the most relevant articles, with a focus on randomized controlled trials (RCTs) and controlled studies that have an impact on the rating. The 11 articles chosen for Structured Decision Making (SDM) are summarized below:

Baird, C., Wagner, D., Healy, T., & Johnson, K. (1999). Risk assessment in child protective services: consensus and actuarial model reliability. Child Welfare, 78(6), 723–748

Type of Study: Validation study
Number of Participants: 80 child abuse/neglect reports

Population:

  • Age — Not specified
  • Race/Ethnicity — Not specified
  • Gender — Not specified
  • Status — Participants were families involved in child welfare systems.

Location/Institution: Alameda County, California; Dade County, Florida; Jackson County, Missouri; and Macomb, Muskegon, Ottawa, and Wayne Counties in Michigan

Summary: (To include comparison groups, outcomes, measures, notable limitations)
Three widely used child protective service risk assessment models, two consensus-based Washington Risk Assessment Matrix (WRAM), and the California Family Assessment Factor Analysis (CFAFA), and one actuarial, the Michigan Structured Decision Making (SDM) System’s Family Risk Assessment of Abuse and Neglect (FRAAN) were examined to determine their reliability. Rates of subsequent investigations, substantiations, and placements were computed for cases classified at low, moderate, and high risk levels in each model. Results indicate that although no system approached 100% interrater reliability, raters employing the actuarial model made consistent estimates of risk for a high percentage of the cases they assessed, and interrater reliability for the actuarial model was much higher than that of the other systems. Limitations include the absence of blinding to previous risk assessments and a lack of population descriptive data.

Length of postintervention follow-up: None.

Baird, C., & Wagner, D. (2000). The relative validity of actuarial-and consensus-based risk assessment systems. Children and Youth Services Review, 22(11–12), 839–871. https://doi.org/10.1016/S0190-7409(00)00122-5

Type of Study: Validation study
Number of Participants: 1,400 child abuse/neglect reports

Population:

  • Age — Not specified
  • Race/Ethnicity — Not specified
  • Gender — Not specified
  • Status — Participants were families involved in child welfare systems.

Location/Institution: Alameda County, California; Dade County, Florida; Jackson County, Missouri; and Macomb, Muskegon, Ottawa, and Wayne Counties in Michigan

Summary: (To include comparison groups, outcomes, measures, notable limitations)
This study is the first to directly compare the relative validity of these two approaches. Three risk assessment instruments were completed on cohorts of cases from four different jurisdictions. Two of the instruments were consensus-based (Washington Risk Assessment Matrix and the California Family Assessment Factor Analysis), and one was actuarial, the Michigan Structured Decision Making (SDM) System’s Family Risk Assessment of Abuse and Neglect Outcome information was collected over an 18-month follow-up period. Rates of subsequent investigations, substantiations, and placements were computed for cases classified at low-, moderate-, and high-risk levels in each model. Results clearly demonstrate that SDM more accurately classifies cases to different risk levels. Limitations include the absence of blinding to previous risk assessments and a lack of population descriptive data.

Length of postintervention follow-up: 18 months.

Johnson, K., & Wagner, D. (2005). Evaluation of Michigan's foster care case management system. Research on Social Work Practice, 15(5), 372-380. https://doi.org/10.1177/1049731505276312

Type of Study: Pretest-posttest study with a nonequivalent control group
Number of Participants: 1,722

Population:

  • Age — 0-18 years
  • Race/Ethnicity — SDM: 79.5% White, 19.1% African American, and 5% Other/Unknown; Comparison: 49.1% White, 43.9% African American, and 7% Other/Unknown
  • Gender — Not specified
  • Status — Participants were children in foster care at the beginning of the intervention.

Location/Institution: Michigan

Summary: (To include comparison groups, outcomes, measures, notable limitations)
The purpose of this study was to assess the efficacy of Structured Decision Making (SDM). Counties implementing SDM were matched with counties using standard case management on demographics including race, percentage receiving public assistance, percentage below poverty line, and percentage in rural areas. They were also matched on administrative characteristics such as foster care caseload, ratio of cases per foster care worker, and percentage of cases managed under private agencies. Results showed a significantly higher percentage of permanent placements for the counties using SDM than for the comparison group. This difference held when controlling for age, ethnicity, and initial type of placement. A greater number of comparison group children re-entered foster care than those in the counties using SDM, although this difference was not statistically significant. Limitations included nonrandomization and generalizability due to ethnicity of participants.

Length of postintervention follow-up: 15 months.

Johnson, W. L. (2011). The validity and utility of the California Family Risk Assessment under practice conditions in the field: A prospective study. Child Abuse & Neglect, 35(1), 18-28. https://doi.org/10.1016/j.chiabu.2010.08.002

Type of Study: Validation study
Number of Participants: 7,685 child abuse/neglect reports

Population:

  • Age — Not specified
  • Race/Ethnicity — Not specified
  • Gender — Not specified
  • Status — Participants were social workers in child welfare systems.

Location/Institution: Los Angeles, Humboldt, Orange, San Luis Obispo, and Sutter counties in California

Summary: (To include comparison groups, outcomes, measures, notable limitations)
This study presents the analysis of the validity and implementation of the California Family Risk Assessment (CFRA; now called Structured Decision Making). The study analyzes reports originating in 5 California counties followed prospectively for 2 years to identify further substantiated child abuse/neglect. Measures of model calibration and discrimination were used to assess CFRA validity and compare its accuracy with the accuracy of clinical predictions made by child welfare workers. Results indicate imperfect but better-than-chance predictive validity was found for the CFRA on a range of measures. For 114 cases, where both CFRA risk assessments and child welfare worker clinical risk assessments were available, the CFRA exhibited evidence of imperfect but better-than-chance predictive validity, while child welfare worker risk assessments were found to be invalid. Child welfare workers overrode CFRA risk assessments in only 114 of 7,685 cases and provided in-home services in statistically significantly larger proportions of higher versus lower risk cases, consistent with heavy reliance on the CFRA. Limitations include the absence of blinding to previous risk assessments and a lack of population descriptive data

Length of postintervention follow-up: None.

Coohey, C., Johnson, K., Renner, L. M., & Easton, S. D. (2012). Actuarial risk assessment in child protective services: Construction methodology and performance criteria. Children and Youth Services Review, 35(1), 151–161. https://doi.org/10.1016/j.childyouth.2012.09.020

Type of Study: Validation study
Number of Participants: 6832 child abuse/neglect reports

Population:

  • Age — Not specified
  • Race/Ethnicity — 73.4% White, 7.1% African American, 4.2% Latino, 1.1% Asian, 0.8% Native American, 0.2% Pacific Islander, 2.9% More than one group, and 10.2% Unknown
  • Gender — Not specified
  • Status — Participants were families involved in child welfare systems.

Location/Institution: Iowa

Summary: (To include comparison groups, outcomes, measures, notable limitations)
This article describes methodology to construct and revise , Colorado's Family Risk Assessment (CFRA) [now called Structured Decision Making (SDM)]; reviews criteria to evaluate the performance of actuarial tools; and applies a methodology and performance criteria in one state. Rates of subsequent investigations, substantiations, and placements were computed for cases classified at low, moderate, and high risk levels in each model. Results indicate that both the adopted and the revised tools had adequate separation and good predictive accuracy for all families and for the state's three largest ethnic/racial groups (White, Latino, and African American). The adopted tool classified relatively few families in the low-risk category; the revised tool distributed families across risk categories. Limitations include unknown inter-rater reliability and external validity and the sample included families with substantiated maltreatment only.

Length of postintervention follow-up: None.

Johnson, K., O'Connor, D., Berry, S., Ramelmeier, D., & Pecora, P. J. (2012). Structuring the decision to accept a child protection report. Journal of Public Child Welfare, 6(2), 191–205. https://doi.org/10.1080/15548732.2012.667736

Type of Study: Validation study
Number of Participants: 46

Population:

  • Age — Not specified
  • Race/Ethnicity — Not specified
  • Gender — Not specified
  • Status — Participants were social workers in child welfare systems.

Location/Institution: Maryland

Summary: (To include comparison groups, outcomes, measures, notable limitations)
Three agencies collaborated to construct, implement, and evaluate Structured Decision Making (SDM) for child protective services intake staff in Maryland. Evaluation activities included reliability testing of the assessment, a qualitative review of screening decisions conducted before and after implementation, and a survey of workers about the assessment and its implementation. Interrater reliability testing among field staff showed high rates of agreement for screening assessment items and the resulting decision. Results indicate that the assessment and associated definitions can help workers make consistent screening decisions when provided with the same information. Limitations include interrater reliability testing, possible sample bias, and lack of follow-up.

Length of postintervention follow-up: None.

Wells, M., & Correia, M. (2012). Reentry into out-of-home care: Implications of child welfare workers’ assessments of risk and safety. Social Work Research, 36(3), 181–195. https://doi.org/10.1093/swr/svs011

Type of Study: Validation study
Number of Participants: 2,507

Population:

  • Age — Not specified
  • Race/Ethnicity — 3.6% Dutch, 21.4% Moroccan, Turkish, 19.6% Surinamese, Antillean, and 25.5% Other (e.g., Cape Verdeans, other Africans, and Eastern Europeans)
  • Gender — Not specified
  • Status — Participants were families involved families with the child welfare system.

Location/Institution: Chicago

Summary: (To include comparison groups, outcomes, measures, notable limitations)
This study examined predictors or reentry to foster care among children and youths who entered foster care between 2001 and 2007. Three sources of administrative data (Chapin Hall Center for Children’s longitudinal files, National Child Abuse and Neglect Data System, and Structured Decision Making [SDM]) from one state was used to assess whether Child Protective Services workers’ risk and safety assessment decisions are predictive of reentry into foster care. Results indicate that cases with current neglect assessments, problems with parenting skills, motivation to improve parenting, safety assessment decision, length of stay, substantiated allegations, and unsubstantiated allegations were likelihood of reentry. Limitations include possible worker error when entering data, missing records, and generalizability to the state data that was collected.

Length of postintervention follow-up: None.

Johnson, W., Clancy, T., & Bastian, P. (2015). Child abuse/neglect risk assessment under field practice conditions: Tests of external and temporal validity and comparison with heart disease prediction. Children and Youth Services Review, 56, 76–85. https://doi.org/10.1016/j.childyouth.2015.06.013

Type of Study: Validation study
Number of Participants: 6,543 child abuse/neglect reports

Population:

  • Age — Not specified
  • Race/Ethnicity — Not specified
  • Gender — Not specified
  • Status — Participants were social workers in child welfare systems.

Location/Institution: San Luis Obispo, Sutter, Orange, Los Angeles, and Humboldt counties

Summary: (To include comparison groups, outcomes, measures, notable limitations)
The purpose of this study was to identify validation design and accuracy assessment standards for medical prognostic models applicable to evaluation of child abuse/neglect (CA/N) risk assessment models. (2) Assess the accuracy of the California Family Risk Assessment (CFRA) [now called Structured Decision Making (SDM)] in predicting CA/N using the foregoing standards. (3) Compare the prediction accuracy of the CFRA with the prediction accuracy of coronary heart disease (CHD) prediction models. Data was used from the California's computerized Child Welfare Services/Case Management System (CWS/CMS). Results indicate that external and temporal validation samples support the accuracy of CFRA prediction of CA/N. Limitations include is the small size (N=236) of the external validation sample.

Length of postintervention follow-up: None.

Mendoza, N. S., Rose, R. A., Geiger, J. M., & Cash, S. J. (2016). Risk assessment with actuarial and clinical methods: Measurement and evidence-based practice. Child Abuse & Neglect, 61, 1–12. https://doi.org/10.1016/j.chiabu.2016.09.004

Type of Study: Validation study
Number of Participants: 2178

Population:

  • Age — Not specified
  • Race/Ethnicity — 76.6% White
  • Gender — Not specified
  • Status — Participants were social workers in child welfare systems

Location/Institution: Ohio

Summary: (To include comparison groups, outcomes, measures, notable limitations)
The purpose of the current study is to compare clinical and actuarial methods of risk assessment used by child welfare workers to make decisions about substantiation and services, the Comprehensive Assessment and Planning Model—Interim Solution(CAPMIS). The tool used in the current study was adapted from the National Council on Crime & Delinquency’s (NCCD)

Length of postintervention follow-up: None.

van der Put, C. E., Hermanns, J., van Rijn-van Gelderen, L., & Sondeijker, F. (2016). Detection of unsafety in families with parental and/or child developmental problems at the start of family support. BMC Psychiatry, 16(1), 15. https://doi.org/10.1186/s12888-016-0715-y

Type of Study: Validation study
Number of Participants: 87,329

Population:

  • Age — Not specified
  • Race/Ethnicity — 33.6% Dutch, 21.4% Moroccan, Turkish, 19.6% Surinamese, Antillean, 25.5% Other (e.g., Cape Verdeans, other Africans, and Eastern Europeans)
  • Gender — Not specified
  • Status — Participants were Dutch families who experienced parenting and/or child developmental problems and were referred by the Centres for Youth and Family for family support.

Location/Institution: Netherlands

Summary: (To include comparison groups, outcomes, measures, notable limitations)
The predictive validity of the California Family Risk Assessment (CFRA) [now called Structured Decision Making (SDM)] was examined in Dutch families who received family support. In addition, the added value of a number of experimental items was examined. Finally, it was examined whether the predictive value of the instrument could be improved by modifying the scoring procedure. Results indicate that about half of the individual CFRA items were not related to future reports of child maltreatment. The predictive validity of the CFRA in predicting future reports of child maltreatment was found to be modest. The addition of some of the experimental items and the modification of the scoring procedure by including only items that were significantly associated with future maltreatment reports resulted in a ‘high’ predictive validity. Limitations include limited financial resources prevented us to verify the 6-month follow-up reports of child maltreatment by field investigation, not every case of child maltreatment is reported to the ARCAN and the number of cases of emotional abuse and neglect may be underreported.

Length of postintervention follow-up: None.

Jenkins, B. Q., Tilbury, C., Hayes, H., & Mazerolle, P. (2018). Factors associated with child protection recurrence in Australia. Child Abuse & Neglect, 81, 181–191. https://doi.org/10.1016/j.chiabu.2018.05.002

Type of Study: Validation study
Number of Participants: 9,608 child abuse/neglect reports

Population:

  • Age — 0–17 years
  • Race/Ethnicity — Not specified
  • Gender — Not specified
  • Status — Participants were families involved in child welfare systems.

Location/Institution: Queensland, Australia

Summary: (To include comparison groups, outcomes, measures, notable limitations)
The aim of the current research was to advance understanding of child protection in Australia by examining the factors associated with recurrence of child protection notifications to the formal child protection system. The risk assessment tool used in this study was the Structured Decision Making (SDM) Family Risk Evaluation in Queensland and known as the SDM Family Risk Assessment. Administrative data were obtained for a sample of 9,608 children first subject to a screened-in report in 2011–2012. Children were followed for 12 months. Cox Proportional Hazard models were used to measure associations between 26 independent variables and four types of recurrence: subsequent reports, subsequent investigations, subsequent substantiations, and subsequent intervention. Factors associated with recurrence in Australia were broadly similar to those identified in other jurisdictions, including reports and substantiation for neglect, younger age, prior child protection involvement in the household, and parental characteristics including drug use, mental health problems, and history of maltreatment as a child. Results indicate that as in previous studies, post-investigative service provision was positively associated with recurrence. In prior US research, race did not predict recurrence. However, in the present study, Indigenous Australian children were significantly more likely to be subject to all types of recurrence measured. Future research on recurrence should aim to disentangle the complex relationships between child protection recurrence, child maltreatment, and service delivery. Recurrence is not a good proxy indicator of child safety. Limitations include utilization of administrative data so it was only possible to analyse the factors that were routinely recorded by practitioners in the course of their work.

Length of postintervention follow-up: None.

Additional References

D’Andrade, A., Austin, M. J., & Benton, A. (2008). Risk and safety assessment in child welfare: Instrument comparisons. Journal of Evidence-Based Social Work, 5(102), 31-56. https://doi.org/10.1300/J394v05n01_03

Shlonsky, A., & Wagner, D. (2005). The next step: Integrating actuarial risk assessment and clinical judgment into an evidence-based practice framework in CPS case management? Children and Youth Services Review, 27, 409-427. https://doi.org/10.1016/j.childyouth.2004.11.007

Wiebush, R., Freitag, R., & Baird, C. (2001). Preventing delinquency through improved child protection services. OJJDP Juvenile Justice Bulletin. U.S. Department of Justice, Office of Juvenile Justice and Delinquency Prevention. https://www.ncjrs.gov/App/Publications/abstract.aspx?ID=187759

Contact Information

Philip Decter
Agency/Affiliation: NCCD Children's Research Center
Website: www.nccdglobal.org/assessment/structured-decision-making-sdm-model
Email:
Phone: (800) 306-6223
Fax: (608) 831-6446

Date Research Evidence Last Reviewed by CEBC: November 2019

Date Program Content Last Reviewed by Program Staff: April 2020

Date Program Originally Loaded onto CEBC: June 2008