Building a Culture of Data Use

1. Building a Culture of Data Use Kathy Hebbeler Donna Spiker Improving Data, Improving Outcomes Conference August 2016

2. Federal Policies State Systems Local/Regional System LeadershipFiscal Policies Professional DevelopmentUse of Data, etc., Practices Interactions of providers with children and families Good outcomes for children and families

3. Good State System Good Practice Good Outcomes Governance Result Quality Standards Finance Implementation of Effective Practices Good outcomes for children with disabilities and their families Building High-Quality Systems Accountability & Quality Improvement Personnel / Workforce Data System For more information about the ECTA System Framework, visit: http://ectacenter.org/sysframe/

4. Thinking about Systems • Has multiple components • The components interact • All of the components are important • Personnel standards • Good fiscal policy • Systems are constantly changing – and they are hard to change. X New coordinators who are wondering what the job entails: Check out the System Framework

6. What do all these people have in common? • All of them make decisions • Their decisions reflect their unique perspective in the system. • Their decisions impact others in the system.

7. Propositions • Good decisions are better than bad decisions • Your decisions combined with others’ decisions are critical to whether children and families achieve good outcomes. • People are more likely to make good decisions when they have good information…and that requires good data.

8. Vision for Data Use Every person who has influence within the system • Has timely access to relevant, complete, and accurate information • Uses that information to improve policy, systems, programs, or practice

9. Examples of data-informed decisions

10. If this vision was achieved… • There are no problems that go unnoticed because no one knows that they are there. • There are no opportunities for improvement that are lost because no one knew that something needed to get better.

11. Continuous Quality Improvement (CQI)

12. Creating conditions that support quality

14. Plan an improvement – and determine how you will know if the improvement is effective • State level • Program level • Child and family

15. Doit - • Implement the improvement • Collect the data Do we need these data on an ongoing basis?

16. Study • Analyze the data • Interpret • Reflect

17. (http://libraryguides.lehigh.edu/TRACseminar/understandinginformation)(http://libraryguides.lehigh.edu/TRACseminar/understandinginformation)

19. DaSy Critical Questions http://dasycenter.sri.com/downloads/DaSy_papers/DaSy_Critical_Questions_FINAL_20151023v2.pdf DaSy/NCSI Data Visualization Tool Kit http://dasycenter.org/data-visualization-toolkit/

21. Moving from Information to Knowledge • Putting meaning on the numbers • Requires understanding what is going on • Requires knowledge and understanding of context

22. https://www.sri.com/work/publications/national-early-intervention-longitudinal-study-neils-final-reporthttps://www.sri.com/work/publications/national-early-intervention-longitudinal-study-neils-final-report

24. Moving from Information to Knowledge • Noticing the unexpected • The numbers do not talk. Somebody has to see something. • Means the user has some sense of what things should look like – and what they shouldn’t • The “jewel” of the anomaly • “How can that be?” • “What’s up with that?”

25. (http://libraryguides.lehigh.edu/TRACseminar/understandinginformation)(http://libraryguides.lehigh.edu/TRACseminar/understandinginformation)

26. Acton what was learned • Possible conclusions and actions: • Well done → Make sure mechanisms are in place to sustain the improvement. Plan another improvement • Mostly there → Tweak if needed and continue to monitor. Maybe plan another improvement. • Not what we wanted →Return to planning and re-think.

27. Key Ingredient for CQI: Leadership • Committed to continuous improvement • Strong, participatory, inclusive • Serve as role models for using data in decision making • Clearly communicate expectations around data use • Recognize that staff time is required to collect, enter, examine and use data.

28. Key Ingredient for CQI: Leadership • Allocate resources to technology needed to house and analyze data. • Provide professional development for staff on understanding, analyzing, and using data. • Create an organizational culture that facilitates continuous data use. • Values learning • Creates a safe space for shared learning through reflection and interpretation of data.

29. DEC Recommended Practices: Leadership • L12. Leaders collaborate with stakeholders to collect and use data for program management and continuous program improvement and to examine the effectiveness of services and supports in improving child and family outcomes.

30. Key Ingredient: Appropriate Data • System is collecting the necessary data elements at the appropriate frequency (See SD4 in DaSy Framework) • Data are of high quality

31. Key Ingredient: Appropriate Technology • The technology (hardware, software) to collect, transmit, store, and analyze the data • Users have ready access to analyzed data • Timely and useful data displays

33. Key Ingredient: Human Capacity • Extent to which staff understand: • What appropriate data are • How to analyze the data • How to make meaning from the data • Knowledge and skills to interpret data (in general) • Knowledge of the context to make sense of EI and ECSE data • How to use the data in meaningful ways to improve the quality of their work.

34. Data System is one component of the state system This component is addressed in the DaSy Data System Framework For more information about the Data System Framework, visit: • http://dasycenter.org/resources/dasy-framework/

35. Where to start to move to CQI • All states have started • All states collect some data • many of you collect a lot of data • Some of you collect all or most of the data elements you need • some don’t

36. Where to start to move to CQI • In some of your states, staff at state and local level have ready access to the data they need • not the case in all states. • Some of you can link data sets to examine some important issues • Most of you cannot

37. Think big if you can • Where do you start? • Wherever it makes sense for your state… • Do you have the resources and the stakeholder support (especially the stakeholders who control the resources) to make a significant change in a short time?

38. Start small if you need to • If not, start incrementally. • Pick a small goal that will allow your state to move toward using data CQI • Add a few data elements • Get a few reports produced quarterly for state use • Get a few reports out to the locals.

42. Special Thanks to…. (in order of appearance) • Tony Chambers • Ovella "Ms.Peaches" Lott • Lisa Backer • Bob Morris • Ann Freiburg and Rita Wahl • Chelsea Guillen

43. And to the Production Team • Staff at the Center for Technology in Education, Johns Hopkins University • Denise Mauzy • Bruce Bull

44. The TA Centers are here to help you. Please contact us.

45. Please complete your conference evaluation when you get home!!! We do use data to inform our decision-making.

46. If you want to build a ship, don’t drum up the people to gather wood, divide the work, and give orders. Teach them to yearn for the vast and endless sea. Antoine De Saint-Exupery

47. Visit the DaSy website at:http://dasycenter.org/ • Like us on Facebook: https://www.facebook.com/dasycenter • Follow us on Twitter:@DaSyCenter

48. The contents of this presentation were developed under a grant from the U.S. Department of Education, #H373Z120002. However, those contents do not necessarily represent the policy of the U.S. Department of Education, and you should not assume endorsement by the Federal Government. Project Officers, Meredith Miceli and Richelle Davis.