Incorporating Head Start Data into Your SLDS

1. Incorporating Head Start Data into Your SLDS • Tuesday, October 30, 2012 • Colleen Murphy, Utah Early Childhood Comprehensive Systems Initiative • Denise Mauzy, Opportunities in a Professional Education Network (OPEN) Initiative at the University of Missouri • June Fox, Wisconsin Department of Public Instruction • Missy Cochenour, State Support Team

2. Today We’re Going to Discuss … What is Head Start? Why integrate Head Start data in your SLDS? State context: Wisconsin, Utah & Missouri What are common challenges in integrating Head Start data? What are best practices in integrating Head Start data? Digging deeper: What are your questions?

3. What is Head Start?

4. What is Head Start? Head Start is … • A federally-funded program that promotes the school readiness of at-risk young children and their families. • The program serves more than 1.1 million children ages birth to five.

5. What is Head Start? Head Start is a federal-to-local program. • Funding comes directly from the government to local grantees in community-based organizations. • While 80 percent of funding comes from the federal government, 20 percent comes from “local match” or “in-kind” contributions from the local community.

6. What is Head Start? Head Start is not … • Administered by states, although some states fund additional Head Start spaces. What governs Head Start? • The Head Start Act, as amended and the Head Start Program Performance Standards and Other Regulations govern Head Start.

7. What is Head Start? Each state has Head Start-State Collaboration Office (HSSCO) Director. • Directors must serve on each State Advisory Council on Early Childhood Education and Care and work to promote collaboration, coordination, and alignment of Head Start programming, services, and/or standards with those of the state’s other early childhood education and care providers.

8. What is Head Start? What data is collected for Head Start? • Program models; • Participant demographics; • Services provided or referred; • Frequency, duration and intensity of services; • Child, family and program outcomes.

9. Why Integrate • Head Start Data • in your SLDS?

10. Why Integrate Head Start Data? Head Start is one piece of a larger early childhood puzzle.

11. Why Integrate Head Start data? Head Start programs are primary partners in SLDSs: • Their data are essential to inform research, policy, and practice. • Without Head Start data, an SLDS could be missing more than 25% of the early childhood population.

12. Why Integrate Head Start Data? Head Start data that can be incorporated in an SLDS includes: Enrollment & Waiting Lists Child Turn-Over (Number, Reason, Health & Dental Insurance Status Home Visits Child Observations IEP/IFSP Referrals & Follow-up (Number, Type, Result, etc.) Staff Turn-Over (Number, Reason, Location, Position) Progress toward School Readiness Goals Parent-Teacher Conferences Meals (menu, cost, nutritional value, etc.) Physicals & Immunizations Budgets & Funding Levels Child Outcomes Case Notes MOUs/MOAs Community Assessment Health services Developmental Screening Results Child Abuse/Neglect Report Rates Child & Family Demographics Attendance Volunteers (Number, Type, Hours) Health Events/Concerns (allergies, contagious disease exposure, etc.) Behavior incidents Dental services Staff Credentials Transportation

13. Why Integrate Head Start data? SLDS integration benefits Head Start, too, by … • Demonstrating the effectiveness of Head Start programs; • Evidencing staff preparation; and • Contributing to strengthening all early childhood services to better prepare children and families for success in school.

14. State Context: • Wisconsin, Utah • & Missouri

15. Context Wisconsin: • Early Childhood Longitudinal Data System (EC LDS) Mission Statement “Wisconsin will be able to measure child outcomes across systems to evaluate young children’s progress and inform policy decisions.” • May 2013 – Conclusion of Planning Phase (Feasibility Study) • ARRA Grant, LDS 3 Grant, Support of Governor’s Early Childhood Advisory Council • Data Roundtable (Stakeholder Outreach and Requirements Gathering) • Identification of EC Data Elements across 37 programs, across three participating agencies (Department of Public Instruction, Department of Health Services, Department of Children and Families)

16. Context Wisconsin: • May 2013 – Conclusion of Planning Phase (Feasibility Study) (continued) • Selection of five overarching policy questions for the EC LDS to answer • Are children, birth to 5, on track to succeed when they enter school and beyond? • Which children and families are and are not being served by which programs/services? • Which children have access to high-quality early childhood programs and services? • What characteristics of programs are associated with positive child outcomes for which children? • What are the education and economic returns on early childhood investments? • Other Recommendations: Governance, System Architecture, Sustainability, Stakeholder Engagement, Etc.

17. Context Wisconsin: • Starts January 2013 – EC LDS Build and Implementation Phase** • Round 2 Race to The Top Grant, Support of Governor’s Early Childhood Advisory Council • Year 1 Highlights – Enhance DHS and DCF Data Environments (years 1-4), Establish Data Governance, Select and Implement Entity Resolution Software (Matching Tool) • Year 2 Highlights – Build and Implement Presentation Layer (Analysis Tools, Dashboards and Reports) For First Set of Data Selected to Answer Key Questions • Year 3 Highlights – Enhance Presentation Layer For Next Set of Data Selected to Answer Key Questions and Presentation Layer Training of Agency Staff • Year 4 Highlights – Enhance Presentation Layer For Next Set of Data Selected to Answer Key Questions and Presentation Layer Training for Local/Public Access ** subject to grant application approval

18. Context Utah: • The mission of the Utah Early Childhood Statewide Data Integration Project is to facilitate data sharing and coordination among early childhood programs in Utah. • Data from the Early Childhood Data System will be pushed annually to the P-20 Data Warehouse. • Data security has become a major factor with Utah’s data integration project. • The Utah Department of Health recently had a major data breach. As a result, all participants are concerned with data security.

19. Context Missouri: • Two year contract from the Missouri Coordinating Board for Early Childhood to the University of Missouri • Two primary goals • Enroll Head Start staff and programs in MOPD System. • Facilitate Head Start participation in state-level data collection efforts and analyses.

20. What Are the Challenges • in Integrating • Head Start Data?

21. What Are the Challenges? • Lack of communication and understanding between Head Start and SLDS; • Head Start data does not align with the data of other Early Childhood programs (i.e., data is by grantee, rather than county or district); • Head Start reluctance to buy into yet another reporting system; • Head start fear that data will discount their programs; • Lack of incentives and resources to expand SLDS work to Head Start.

22. What Are Best Practices • in Integrating • Head Start Data?

23. What Are Best Practices? Communication and Outreach Governance Data-Sharing Agreements Core Data Elements Data Use

24. Communication and Outreach Wisconsin: • Working through the state’s Head Start Collaboration Office and reaching out to it’s Head Start Association • Interest has been generated: WI HSA members want to be involved in future workgroups and to receive updates Utah: • Head Start is represented on all state early childhood committees. • When needed, one-on-one meetings are held to respond to Head Start questions and/or concerns.

25. Communication and Outreach Missouri: • Identified the benefits for all parties in the beginning and explored the challenges as a group • Emphasis on working with statewide partners (HS Association, HSSCO, Child Care Aware, etc.) • Approached the project as a joint planning process • Head Start leaders ask great questions—AND have great solutions • Communicated where we could compromise and look for creative solutions • Secured support from leadership and participation of key data personnel • Site level visits when necessary • Monthly report of activities to the Head Start Advisory Council

26. Governance Wisconsin: • Working on governance structure and overarching MOU for future EC-LDS, including Head Start • Head Start already integrated into YoungStar (WI’s QRIS); when the time is right, data able to be agreed upon and shared Utah: • Head Start representatives are involved in writing governance policies and procedures. • Each data supplier has one vote in approving data requests and in authorizing the use of its data for research requests. Missouri: • Utilizing the Council for Early Childhood/School Age Data and Research Sub-Committee to inform planning processes and establish priorities • Head Start data governed by MOU during this “pilot” process

27. Data Sharing Agreements Wisconsin: • Milwaukee Public Schools is ahead of the state effort in developing their own local EC LDS. • As a Head Start grantee, MPS is actively developing a DSA to include Head Start data within their local EC LDS. Ongoing communication occurs between MPS and the state EC LDS project. Utah: • Agreements are signed by legal representative of each data supplier, including participating Head Start programs. • Data suppliers have the ability to terminate the agreements at any time. Upon termination, UDOH will destroy personally identifiable information.

28. Data Sharing Agreements Missouri: • Frames this effort as a “pilot” • Agreement sunsets after 3 years unless renewed • Clearly defines the role of all parties (e.g., University, DESE, and Head Start agencies) • E.g., who is responsible for parental disclosure • Defines how we may use the data

29. Core Data Elements Wisconsin: • Supports the idea of vendors (such as Child Plus) defining common data elements (Head Start data into CEDS) Utah: • Each data supplier will have an attachment to the data sharing agreement listing data elements it will share with the Early Childhood Data System and the UT Data Alliance P-20 data warehouse. • Each data supplier determines which data elements it is willing to share.

30. Core Data Elements Missouri: • Focus on essential data elements during pilot • Must be common between the 28 agencies • Started with review of PIR • Aligning with CEDS work • Pilot includes two transfers • #1- ID generation/matching and enrollment and attendance (current and historical records • For example, a Head Start agency would need to provide 5 years of data in order to receive feedback about how their children did on the 3rd grade MAP test • #2- child well being (from this point forward)

31. Data Use Wisconsin: • 80% of Head Start data fully integrated into YoungStar (WI’s QRIS). Head Start grantees, affiliated with a child care program, receive an automatic 5 star (highest) rating, if in good standing. • Able to ID Head Start centers in YoungStar for a look at the program level. Utah: • Each data supplier may veto the use of its data for any research request. • The results/findings of all requests are reported to the Data Research and Policy Committee to be approved before being made public. Missouri: • For feedback to programs and research ONLY • MOU includes an analysis plan---any data use outside of the plan would require an amendment to the MOU • Includes a peer review process by the Research Sub-Committee to ensure proper methodology, etc

32. Round Table Discussion • Digging Deeper: • What Are Your • Questions?

33. Contacts & Additional Resources Contact information: Colleen Murphy, cmurphy@utah.gov Denise Mauzy, MauzyD@missouri.edu June Fox, June.Fox@dpi.wi.gov Missy Cochenour, missy.cochenour@sst-slds.org For more information on Incorporating Head Start into Your SLDS: SLDS Topical Webinar Summary: Head Start and SLDS: Getting to Know You: http://nces.ed.gov/programs/slds/pdf/Headstart_and_SLDS.pdf Head Start Website: http://eclkc.ohs.acf.hhs.gov/hslc Head Start-State Collaboration Offices: http://eclkc.ohs.acf.hhs.gov/hslc/states/collaboration