The effective use of Part C and Part B 619 data is fundamental to the achievement of positive outcomes for children with disabilities and families. Achieving positive outcomes for all children with disabilities requires equitable access to IDEA services and the individualized and equitable provision of those services and supports. All high-quality state systems should be using data regularly to see if there are differences across subgroups which could be an indication that the system is not equitable and to identify the root causes for those differences and inform solutions. Part C and Part B 619 state staff need the knowledge and skills to formulate and answer critical questions about equitable access, services and supports, and positive outcomes for the overall population of children and families and for each of the various subgroups in the state.
The purpose of the Data Analysis and Use subcomponent is to assist state leaders in facilitating ongoing use of quality Part C and Part B 619 data for program accountability, program improvement, and program operations at state and local levels. Part C and Part B 619 state and local staff benefit from using data effectively, but they need knowledge and skills to be able to formulate critical questions about the outcomes of services provided. They also need to exhibit data leadership by setting expectations and supporting the conditions that will lead to effective data use at state and local levels. Effective data use requires ongoing planning, analysis, and dissemination of data products. In many cases, data become more valuable when they are linked with other data, creating additional information from which new data products can be developed (e.g., child outcome data with child service data). Data products are defined as all types of materials containing data, such as, for example, data tables, presentations, and reports.
Linking data with other data (e.g., child outcome data with child service data, Part C with 619 data) allows the state to answer critical questions that could not be answered by either data set alone. As data leaders, Part C and Part B 619 state staff need to understand the power and potential concerns associated with linked data and be able to actively participate in planning efforts that involve their linking program’s data with other data sets.
An assumption underlying the framework is that many different kinds of individuals, including those who have been historically underserved, should understand and use data. A data user is any person who accesses the data in any form, including raw data, data tables, data displays, reports, or any other data products. To be a skilled data user, individuals need professional development and access to technical expertise that supports their effective implementation. All data must be shared and used in compliance with data governance policies and with careful attention to the protection of personally identifiable information.
To achieve positive outcomes based on continuous improvement of programs and systems, the state needs to ensure availability of quality data; analyze, prepare, and disseminate a variety of data products; and provide leadership to build the capacity of state and local staff and stakeholders for effective data use.
This subcomponent consists of three sections. The first section, Data Availability, addresses activities that ensure that users of the data have the quality data they need when they need it. Next, the Data Analysis section addresses activities involving planning and conducting data analyses that meet the needs of the data users. The third section addresses Data Leadership and Data Use, the activities that support creating and maintaining the conditions for a culture of data use at state and local levels.
Section 1: Data Availability
Quality Indicator DU1
Part C/619 state staff implement the processes required to ensure quality data are available for analyses.
|DU1 – Elements of Quality|
|DU1a||All data sources are identified and documented.|
|DU1b||Clear, timely, and necessary guidance is provided for all data collections.|
|DU1c||State and local staff are trained on data collection and submission processes.|
|DU1d||Approved processes are in place to meet data requests of potential users (e.g., agency staff, researchers, legislators).|
|DU1e||A schedule or timeline is developed for accessing and preparing data for all required data analysis activities.|
|DU1f||Processes required to ensure quality data are reviewed and revised as needed.|
Section 2: Data Analysis
Quality Indicator DU2
Part C/619 state staff plan and prepare for data analyses.
|DU2 – Elements of Quality|
|DU2a||The purposes for the analyses are identified, including the critical questions to be addressed.|
|DU2b||Plans for data analysis routinely include critical questions to intentionally examine equitable access, services and supports, and outcomes.|
|DU2c||The type and format of data products that will be used to disseminate results of the analyses are identified.|
|DU2d||Data are reviewed and their completeness, accuracy, and timeliness are verified.|
|DU2e||Data analysis methods that are appropriate for the purpose and use of the data are identified.|
|DU2f||Data analysis plans are reviewed by individuals with relevant technical and programmatic expertise.|
Quality Indicator DU3
Part C/619 state staff conduct data analyses that meet the needs of the state agency and other users.
|DU3 – Elements of Quality|
|DU3a||Analyses are conducted consistent with the attributes of the data (e.g., data quality, significance levels, sample size), intended purposes, and the planned data products.|
|DU3b||The strengths and possible limitations of the analyses are identified.|
|DU3c||Results of the analyses are reviewed by individuals with relevant technical and programmatic expertise including the potential risks of misinterpretation.|
|DU3d||Data products are developed that meet the needs of intended users, incorporating where appropriate:
|DU3e||Disclosure avoidance techniques are used to ensure that personally identifiable information (PII) is protected in accordance with federal and state requirements in all data products.|
|DU3f||Documentation is developed to support future replication of the analyses conducted (e.g., data elements, tools and methods used, strengths/limitations of data analysis and results, data products developed) where applicable.|
Section 3: Data Leadership and Data Use
Quality Indicator DU4
State Part C/619 coordinators function as data leaders to create and maintain the conditions for a culture of data use at the state level.
|DU4 – Elements of Quality|
|DU4a||Staff have the knowledge and skills necessary to use data to inform decision-making, including using data to examine equitable access, services and supports, and outcomes.|
|DU4b||A commitment to using data for decision-making exists throughout the agency.|
|DU4c||Data are high quality and comprehensive.|
|DU4d||Data products (both routine and ad hoc) are available and timely.|
|DU4e||Data are routinely made available across administrative units for collaborative use (e.g., monitoring, fiscal, contracts, programs).|
|DU4f||The strengths and limitations of the analyses and the potential risks of misinterpretation are shared with users of the data products (e.g., data quality, significance levels, small sample size, comparative analyses such as by race, ethnicity, disability characteristics).|
|DU4g||Staff participate in efforts to share IDEA data with and access other early childhood data across programs, agencies, or initiatives (e.g., Medicaid, ECIDS, Child Welfare, EHDI, SLDS, Education).|
Quality Indicator DU5
Part C/619 state staff lead an ongoing data-informed decision-making process (i.e., review of data analyses, interpret results, and make decisions informed by the data).
|DU5 – Elements of Quality|
|DU5a||Effective and routine processes for data-informed decision-making have been adopted (e.g., Plan Do Study Act, Change Management).|
|DU5b||Processes for data-informed decision-making are implemented consistently by individuals and teams.|
|DU5c||Stakeholder groups that represent the full range of diversity in the state, especially those who have been historically underserved, participate in data-informed decision-making processes as appropriate to the topic.|
|DU5d||Data from cross-program and cross-agency partnerships are used for program improvement.|
|DU5e||Processes for data-informed decision-making are reviewed and revised as needed.|
|DU5f||Data-informed decision-making processes routinely and intentionally use data to examine equitable access, experiences, and outcomes.|
Quality Indicator DU6
Part C/619 state staff support local programs or districts in building a culture of data use.
|DU6 – Elements of Quality|
|DU6a||Professional development opportunities are available to build data skills of local programs or district administrators, staff, and stakeholders.|
|DU6b||Supports are provided to ensure data needed by local program or districts to inform decisions are high quality and comprehensive.|
|DU6c||Data products and displays for local programs and districts are available and timely.|
|DU6d||Supports are provided to local programs or districts to engage stakeholders in the ongoing use of data.|
|DU6e.||Supports are provided to create and sustain local use of data for decision-making by individuals and teams.|
|DU6f||Supports are provided to local programs or districts to implement data-informed decision-making processes that routinely and intentionally use data to examine equitable access, services and supports, and outcomes.|
|DU6g||Supports are reviewed and revised as needed based on local program or district feedback.|
Resources Related to Data Analysis and Use
- Critical QuestionsThis DaSy brief describes questions a state data system should be able to answer.Read more
- Data Visualization ToolkitThis DaSy toolkit provides guidance for effectively creating and presenting data visuals.Read more
- Planning, Conducting, and Documenting Data Analysis for Program ImprovementThis 2015 document was developed to help technical assistance (TA) providers and state staff define and limit the scope of data analysis for program improvement ...Read more
- Data Meeting ToolkitThis toolkit is a suite of tools that groups can use to guide conversation around data and support databased decisionmaking. The toolkit provides resources to support ...Read more
- Data Culture ToolkitThe DaSy toolkit is a resource containing information, guidance, and templates to help Part C and Part B 619 program staff build effective data teams ...Read more
- Early Childhood Data Use Assessment ToolThis resource is designed to identify and improve data use skills among early childhood education (ECE) program staff so that they can use data to ...Read more
- Answering Key Questions with an Early Childhood Data SystemThis 2013 issue brief describes a 7-step process to design and use essential questions in an early childhood data system. Suggested stakeholders, their roles, and ...Read more
- Data use for continuous quality improvement: What the Head Start field can learn from other disciplines, a literature review and conceptual frameworkThis report includes a comprehensive literature review and conceptual framework produced as part of the Head Start Leadership, Excellence, and Data Systems project. The review ...Read more