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Solving The Data Puzzle: A “How To” Guide for Cross-System Collaborations Effective Models for Sharing Data &

Solving The Data Puzzle: A “How To” Guide for Cross-System Collaborations Effective Models for Sharing Data & Improving Child Welfare Outcomes Maura McInerney, Esq. Education Law Center November 4, 2011 . http://www.abanet.org/child/education/.

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Solving The Data Puzzle: A “How To” Guide for Cross-System Collaborations Effective Models for Sharing Data &

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  1. Solving The Data Puzzle: A “How To” Guide for Cross-System Collaborations Effective Models for Sharing Data & Improving Child Welfare Outcomes Maura McInerney,Esq.Education Law Center November 4, 2011

  2. http://www.abanet.org/child/education/

  3. Legal Center for Foster Care & Education A joint project of the ABA, Education Law Center, Juvenile Law Center in collaboration with Casey Family Programs, Annie E. Casey Foundation & Stuart Foundation. A national technical assistance resource and information clearinghouse on legal and policy matters affecting the education of children and youth in out-of-home care Website: www.abanet.org/child/education

  4. Data: The Key to Change ….. • Only one third receive high school diploma in four years; • Twice as likely to drop out • Philadelphia study: 75.2% of youth in care dropped out of high school in 2005 • 2-4 times as likely to repeat a grade • California study: 83% of children in care in Los Angeles were held back in school by the third grade • Significantly below their peers on standardized tests • lower reading levels and lower grades in core academic subjects • While 70% of foster youth dream of attending college, 7-13% gain access to any higher education programs and 2% obtain bachelor’s degrees.

  5. What Sharing Data Can Do For You • Indentify systemic problems • Develop effective policies & priorities to • Improve education outcomes • Increase accountability of systems • Target funding (e.g., school stability) • Increase and target $$ for specific goals • Educate and facilitate collaboration among multiple systems: Education, Child Welfare, Juvenile Justice, Employment, Job Training, Vocational, etc.

  6. What Sharing Student-level Data Can Do: • Identify individual educational needs of child • Track child over time and through systems • Trigger prompt intervention • Inform other decisions (e.g., placement and transition goals) • Enhance and improve delivery of services to individual child

  7. What Child Welfare Can Learn from Education Data • Are we meeting our legal mandates for ensuring attendance and school stability? • What do we need to change: Is there a correlation between educational failure and type of placement, length of placement, multiple school moves, lack of education advocate, emotional/behavioral problems, failed adoption; impact of school discipline, improve transition planning re education issues. • What is the impact of: • Prompt enrollment, school stability, trauma-informed curriculum; positive behavioral supports • Longitudinal data: track children through school AND across systems – employment, medical etc.

  8. Child Welfare Agencies: Well-being & Permanency Outcomes • Identify changes made in performance and practice since previous Statewide Assessment such as initiatives/strategies implemented by the State and ensure compliance with requirements of Fostering Connections, CFSRs, AFCARs • **Provide quality assurance results or other data abouteducational assessments and services(how educational needs are assessed; inclusion of educational needs in the case plan and documentation in the child's record; what services the agency provides, role of bio and foster parent)

  9. What Education Can Learn By Sharing Data • What are the barriers to educational success for this student population? Are they promptly enrolled, approriately placed? • Are there disproportionate referrals to alternative education or cyber programs? Are they able to equally access vocational technical programs, challenging courses etc.? • How can schools address common barriers and improve outcomes through new policies, procedures etc. • Are additional services/supports needed (e.g., credit recovery) • Improve collaborations with child welfare & expand access to child welfare-based services • Teacher development training • Curriculum changes

  10. What Courts Can Learn From Sharing Data • Percentage of hearings where the child’s education was addressed • Number of school transfers while under court jurisdiction • Percentage of children in each type of school placement while under court jurisdiction • Percentage of children attending school • Percentage of children whose GPA declined or improved while under court jurisdiction • Percentage of children whose attendance rate declined under court jurisdiction • Percentage of children under court jurisdiction ages 0-3 referred to Early Intervention • Percentage of children under court jurisdiction ages 0-3 enrolled in Early Intervention • Percentage of children under court jurisdiction receiving special education services • Percentage of children under court jurisdiction that referred for evaluation for spec ed. • Percentage of children suspended from school and impact on living placement • Percentage of children expelled from school & impact on placement • Percentage of children who graduate from High School/GED programs • Percentage of children accepted into a higher education program

  11. Look at Your System:What Data Is Being Collected, By Whom and to What End? What is Education Collecting? What isChild Welfare Collecting? What Are Courts Sharing? • What is the purpose of the data collection? • Where/how is the information maintained? • How is it currently being used? • What child welfare data relates to the educational outcomes of children in care? • How could current data be revised/expanded to improve educational outcomes for children in care? • How could it be shared across systems?

  12. What Could Systems Collect/Share • Type of educational placement: public school, residential settings (on-site school, homebound etc.) • School completion rates: Drop out, years to complete high school; reasons for dropping out and at what age • Credit Issues: Document problems with credits, obtaining high school diploma • Transition Readiness: level of education, life skills training, transition plans.

  13. What Could The Systems Collect/Share • School Mobility: Whether living placement resulted in school change & re-enrollment • Special Ed: Early intervention; evaluations requested/conducted; special education services delivered as child moves; type of learning/devp’l disability; decisionmaker • Early ChildhoodEducation: Participation in Headstart/other programs: what age/how long • Discipline: Suspensions, expulsions, alternative education for disruptive youth

  14. What is Education Already Collecting • All States Collect Data • NCLB: No Child Left Behind / IDEA • Electronically Maintained • Student Specific Identification Numbers • Each State May Collect • Additional Data (e.g., discipline info, links to other agencies)

  15. No Child Left Behind Act: What is It? • Seeks to improve educational performance and eliminate achievement gaps between groups of students. • Requires States to implement accountability systems at the state, school district and school level. • Strongly endorses use of longitudinal data: • “Each State may incorporate the data from assessments into longitudinal data systems that link student test scores, length of enrollment and graduation records over time.” • U.S. Dept. of Ed provides funding to states to develop systems to link records over time OR to identify best educational practices. See http://ies.ed.gov/funding/

  16. Data Already Collected Under NCLB • Attendance: Days “absent without excuse” and days enrolledin school • School Enrollment: Tracks student mobility, enrollment delays & grade level designation at time of enrollment • Academic Progress* Standardized scores • Special Education* Disability & Services • Program Template: Participation in remedial & other programs (Title I, HS) * = May be separate data system in your state

  17. “Student” Level Data • Gender • Race/Ethnicity • Student Status – Court placed “or” alt ed. • Economic status (Free/Reduced Lunch Program) • Educationally Disadvantaged under Career and Technical Education programs • Plan 504 Indicator/Special Ed • LEP Participation/English Proficiency/Language Breakdown/Language/ Home Language Code • Courses – Advanced courses only • Grade retention • Expected Graduation, Graduation Status Code & Type of Diploma   • Expected Post Graduate Activity

  18. What Does Each State’s Data Already Tells Us • Number of times children change schools • Attendance • Grade retention & eligibility for supplemental education services • State test proficiency in core subjects • Special Education & LEP participation • Participation in specific remedial programs • Graduation status & expected post-secondary • Drop out & graduation rates

  19. What Could Education Collect • “Prompt” Enrollment (FL example) • Truancy Rates under State Law • School Performance (e.g., San Diego) • Special Education – (evaluation requested) • Academic Progress – expanded definition • Program Data – vocational & ESY • Course enrollment (beyond AP courses) • Credit transfers • Discipline placements in school • On-time graduation rates & higher ed data

  20. What’s Happening In YOUR State • Data Quality Campaign • http://www.dataqualitycampaign.org/survey_results/index.cfm • Education Commission of the States • http://mb2.ecs.org/reports/Report.aspx?id=913

  21. Data Sharing Action Plan • Step I: Identify Subset of Children • Step II: Child Welfare System’s Data • Step III: Education’s Data: Can Education disaggregate non-student specific data using: • Social security nos. (matched with student IDs) • Residency codes – already in Education system • Address/name cross match • Other system • Step IV: Can data be shared across systems? What agreements? What are the barriers? • Step V: Can longitudinal data track these children over time & after they age out?

  22. Barriers to Sharing Data & Information Across Systems: Real & Perceived Child Abuse Prevention and Treatment Act42 U.S.C. § 5101 et. seq.; § 5116 et. seq. • Purpose: Provides guidance to states related to their child protective services systems, including: reporting, investigating, supporting collaboration among agencies, and specifying confidentiality and information sharing. • Allows for information sharing in two ways: • When a state statute* authorizes the sharing of child welfare information with the school system • When school system has a need for limited information to protect the child from abuse and neglect. *Supports and enhances collaboration among agencies, including linkages with education systems

  23. Sharing Information:Real & Perceived Barriers Family Educational Rights and Privacy Act 20 U.S.C. § 1233g; 34 CFR Part 99 • Purpose: to protect privacy interests of parents and students regarding the students’ education records • Parent’s have the right to share or refuse to share records • Exceptions to parental consent

  24. What Education Records Can Be Shared with Child Welfare: • Non-student specific data • Directory Information • If It qualifies as an education record, • Need parent consent • Parental Consent Form (common practice: time of placement) • OR falls under FERPA exceptions to consent (court order is one of the exceptions)

  25. FERPA Definitions • Education records: Records that are directly related to a student and maintained by an educational agency or institution, or by a party acting for the agency or institution. See 34 CFR § 99.3 • Parent : Natural parent, a guardian, or an individual acting as a parent in the absence of a parent or a guardian.

  26. FERPA CONSENT NOT REQUIRED:Non-personally identifiable Information Student is identified by non-personal identifier • Identifier itself is not a scrambled Soc. Sec. unless such identifiers are protected by written agreements reflecting generally accepted confidentiality standards within the research community; and • cannot be linked to an student by anyone who does not have access to the linking key; • data file is populated by data from education records in a manner that ensures that identity of any student is not easily traceable.

  27. FERPA Exceptions (15) • Directory Information (subject to Opt-out) • name, address, phone, date and place of birth, participation in officially recognized activities and sports, and dates of attendance. • Law Enforcement Exception: disclosure to state and local authorities within department of juvenile justice • Emergency Exception: Disclosure to “appropriate parties” in connection with “emergency” to protect health and safety of student or other persons; • Judicial order or subpoena: Comply with court order ** • With notice of disclosure to parent/student

  28. FERPA Compliance Tips • Parental Consent Form • Must notify parent of what they are sharing and with whom, for what purpose & duration • Writing must be clear & user friendly • Court Order • MUST be specific (not CW determines educat.) • Individualized (CANNOT be blanket order) • Reflect notice to FERPA parent • May limit scope of education records or use FERPA definition

  29. FERPA: Proposed Amendments • Create a limited exception to parental notification and consent requirements permitting disclosure to child welfare where a student has been adjudicated dependent, the agency has legal custody of the child in out-of-home care, and the child’s parent or eligible student has received written notice of the proposed release • Permit redisclosure where a child welfare agency obtains education records pursuant to § 99.31(17) to redisclose records to foster parents, group home caseworkers, and other individuals responsible for the education, care or treatment of the student.

  30. FERPA: Proposed Amendments • Amend “eligible student” definition in 34 C.F.R. § 99.3 to include youth who meet the McKinney-Vento definition of “unaccompanied youth” • Include IDEA parents in the definition of parent under FERPA. • Expand research exception.

  31. Sharing Information To Improve Educational Outcomes • Education to Child Welfare • Child Welfare to Ed • Joint Research • Common Data System Accessed by Multiple Agencies (with varying levels of accessibility)

  32. Sharing Individual Student Data • Court order, other exception or written consent embedded as a matter of practice • MOU sets forth • Purpose and limitations of disclosure (expected use) & duration • Who will access information and how • Protects against redisclosure to 3rd parties • Technological security protections/firewalls • Retention of records • Governance

  33. Building Political Will • Cost of NOT sharing information • Anecdotal evidence, statewide data • Better Access = Better Outcomes: Examples • Child welfare, Educational, Permanency & Life • Ensure privacy & compliance w/ fidelity • Ensure compliance with state mandates • Fostering Connections/McKinney/CFSRs • It WILL Reduce Costs: Cost of dropout (prison, crime, drugs) & reduce time in foster care

  34. Examples of Data Collection & Information Sharing • Washington State • Florida Department of Education • Utah • West Virginia • Pima County, AZ • California • Los Angeles Education Coordinating Council • San Diego • Fresno

  35. How Can We Do This? • Tools • Solving the Data Puzzle: http://www.abanet.org/child/education/publications/solvingthedatapuzzle.pdf • Mythbusting: Breaking Down Confidentiality and Decision-Making Barriers to Meet the Education Needs of Children in Foster Care  Author: Kathleen McNaughtwww.abanet.org/child/education • Funding Opportunities

  36. Contact Information Maura McInerney Education Law Center mmcinerney@elc-pa.org www.elc-pa.org 1315 Walnut Street Suite 400 Philadelphia, PA 19107 215-238-6970 Ext. 316

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