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Inter-agency data sharing and protection: Measuring child well-being in the United States. Michael J. Lawler, MSW, PhD University of South Dakota, USA Gail S. Goodman, PhD, Ingrid M. Cordon, PhD, & Shay O’Brien, MSW University of California, Davis, USA.

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inter agency data sharing and protection measuring child well being in the united states

Inter-agency data sharing and protection: Measuring child well-being in the United States

Michael J. Lawler, MSW, PhD

University of South Dakota, USA

Gail S. Goodman, PhD, Ingrid M. Cordon, PhD, & Shay O’Brien, MSW

University of California, Davis, USA

measuring child well being for child welfare services in the us
Measuring child well-being for child welfare services in the US

Adoption and Safe Families Act (1997) +

Child Welfare Indicators Research (e.g., Land et al., 2001) +

Evidence Based Practice (e.g., IOM, 2001)+

Belief in the impact of data (e.g., O’Hare, 2008)

= US Child and Family Services Reviews (first round completed in 2004)

child and family service reviews cfsr for child welfare services
Child and Family Service Reviews (CFSR) for child welfare services
  • Safety – Lack of abuse, neglect
  • Permanency – Home with family, adoption
  • Family and Child well-being – Health, Education, Mental Health, Criminal history
  • Plus, many states adopted additional measures and operational definitions
  • No state met all CFSR standards for safety, permanency, & well-being
project description
Project Description
  • California Department of Social Services contracted with the University of California, Davis for two phases of the project:
    • Phase I: Inter-agency data sharing between California Health & Human Services state and county (58 counties) agencies (Wilson, Goodman, & Lawler, 2006). Can we?
    • Phase II: Data sharing and linkages between agencies and national best practices (Goodman et al., 2009). How can we?
methods
Methods
  • Review of research literature and federal and state regulations
  • Structured interviews with county, state, tribal, and national agencies
  • Case studies review
  • Expert panels
different levels of measuring child welfare outcomes
Different levels of measuring child welfare outcomes
  • Safety – Federal reporting of child abuse and neglect (individual and aggregate)*
  • Permanency – Federal reporting of federally supported child placements (individual and aggregate)*
  • Well-being – Decentralized across jurisdictions (states, counties, cities, school districts). Some data have federal reporting (mostly aggregate)
  • *Measured well by UC Berkeley
decentralized social welfare agencies
Decentralized social welfare agencies
  • California as an example:
  • Health & Human Services –
    • 6 state agencies (Mental Health, Social Services, Alcohol and Drug Programs, Developmental Disabilities, Health Care Services, Public Health)
    • 58 counties with those same agencies
    • Overall population of 36 million
    • 90,000 children in out of home care (foster care)
decentralized education
Decentralized education
  • California as an example:
  • Education
    • State department of Education
    • 58 county Education offices
    • Approximately 1,000 school districts and 9,000 schools
    • 7 million students
protections for child well being data
Protections for child well-being data
  • Health Insurance Portability and Accountability Act (HIPAA) – Protects healthcare information
  • Family Educational Rights and Privacy Act (FERPA) – Protects educational information
  • Both protect rights but can prevent agencies from sharing with each other, especially when not mandated to share
data challenges for agencies in the us
Data challenges for agencies in the US
  • Legally, agencies cannot act outside the power delegated to them under statute (Dawes, 1996)
  • HIPAA and FERPA, and potential litigation, inhibit broader interpretations of statutes
  • “Data people” and “program people” designations may affect data quality
  • Departmental and professional silos
data sharing solutions
Data sharing solutions
  • Re-conceptualize data sharing in terms of both client-oriented and operations-oriented to reflect program and data
  • Direct connections between case management and performance management contribute to better data quality and commitments to data sharing
  • Example - San Diego County, California
data sharing solutions1
Data sharing solutions
  • Short-range goal setting
    • Memoranda of Understanding between entities
    • Court-ordered agreements
    • HIPAA Business Associate Agreements
    • Small, focused data workgroups
    • Sampling for some measures
    • Examples – Los Angeles County, Santa Clara County, California
data sharing solutions2
Data sharing solutions
  • Long-range goal setting
    • Federal and state level advocacy for reinterpretation of statutes
    • Greater standardization of data elements, collection processes, and languages
    • Investment in human resources for data management
    • Bringing together technology, policy, and legal, as well as political will
    • Example – Colorado’s “Virtual Court”
data sharing solutions3
Data sharing solutions
  • Use of Centralized Date Warehouses
    • Can be used as one-stop option for multiple data sources entered and matched confidentially for individual and aggregate data (McDonald & Associates, 2008)
    • Examples – Allegheny County, Pennsylvania, National Center for Health Statistics, Department of Health Care Services, California
references
References
  • Adoption and Safe Families Act (1997). Public Law No. 105-89, 42 USC § 1305.
  • Dawes, S. (1996). Interagency information sharing: Expected benefits, manageable risks. Journal of Policy Analysis and Management, 15, 377-394.
  • Goodman, G.S., Lawler, M.J., O’Brien, S., Wilson, K., Cordon, I.M., & Iandoli, C.C. (2009). California Department of Social Services and Child Welfare Council Data Linkages Project. Sacramento, CA: California Department of Social Services.
  • Institute of Medicine (2001). Crossing the quality chasm: A new health system for the 21st Century. Washington, DC: Author.
  • Land, K.C., Lamb, V.L., & Mustillo, S.K. (2001). Child and youth well being in the United States, 1975-1998: some findings from a new index. Social Indicators Research, 56, 241-320.
  • McDonald, W.R., & Associates (2008). Analysis of existing data collection programs and data warehouse efforts. Reportsubmitted to Casey Family Programs on March 28, 2008. Sacramento: Author.
  • O’Hare, W.P. (2008). Measuring the impact of child indicators. Child Indicators Research, 1, 387-396.
  • Wilson, K., Goodman, G.S., & Lawler, M.J. (2006). Interagency measurement of child well-being. Sacramento, CA: California Department of Social Services.