Authors: Tony Ruggiero & Leah Piatt

The July 30, 2025, IDEA Part C Child Count and Settings data submission to the Office of Special Education Programs via EDPass is coming soon. The IDEA Part C Child Count and Settings collection consists of two components: the Child Count data, which reflect the number of children receiving early intervention services; and the Settings data, which report on the primary setting where children receive early intervention services i.e., home, community-based setting, and other (clinical setting or other non-natural environment).

For Part C Data Managers to be efficient in their collection and preparation of these 618 data, they should monitor and assess the data collection throughout the collection cycle. This blog post outlines considerations for making the submission accurate, complete, and timely (ACT).

While the deadline for submission is clear, the timeline for reporting is longer. If applied correctly, this timeline will allow for an ACT submission. It is important to adhere to a schedule of tasks to avoid missing federal deadlines, limit mistakes in reporting, and ensure data quality. Documenting clear roles and responsibility while establishing data processes will ensure that required data, deadlines, and submission formats are delineated at each stage of the data collection.

Further, for an IDEA Part C Child Count and Settings submission, there are continuous activities that occur before, during, and after the data collection to ensure high-quality data by preventing, detecting, and repairing inaccurate collections.¹ Here are some considerations for collecting data using the Prevent, Detect, and Repair method.

Prevent: Before the data collection begins, there are processes to ensure data are accurate and complete. The data system should have data entry screens with data standards that include in-field and across-field data quality parameters to prevent errors at the point of entry.

Detect: During data collection, it is important to implement a process with timelines that includes state and local staff for data cleaning and editing. For example, a state Part C Data Manager might send a monthly report to local agencies to address missing and incorrect data or missing records. The key to the Detect stage is the collaboration between state and local staff. It should not be viewed as only a state or local initiative.

This process should be used in conjunction with the Prevent stage and should include data quality analysis. The processes will allow for the identification of data anomalies within the data sets. It is important to remember that not all anomalies are incorrect data; they can often show areas that can be improved or adjusted in policy changes moving forward.

Repair: After data collection, the data are used to create reports. Sometimes, reports have errors that need to be corrected or repaired. For example, while using the data in a report, a data consumer may notice errors but may or may not report the errors.

When errors are reported, they must be noted, and the issues can be addressed in future iterations of the data collection cycle. However, the Repair stage should be avoided as much as possible through strong Prevent and Detect stages.

The process to collect the Part C Child Count and Settings data is a year-round endeavor that must be a collaborative effort between the Lead Agency and Local Early Intervention programs. The activities that take place before, during, and after data collection will go a long way in terms of establishing relationships and producing high-quality data that can be used for reporting and to make program decisions.

To support your efforts, DaSy will host weekly Part C Child Count and Settings Office Hours every Wednesday at 3:00–4:00 p.m. ET, from June 4 through July 30. As you prepare to submit your Child Count and Settings data by July 30, remember that DaSy is here to help!

Intended Audience

Part C State Data Managers, staff, and coordinators, TA specialists and others

DaSy Center Resources for ongoing learning

• Part C Data Processes Toolkit
• Data Leadership Competencies
• DaSy Child Count and Settings tool
• EDFacts Child Count and Settings File Specifications FS902, FS903, FS904, FS905 (EDFacts File Specifications SY 2024-25 | U.S. Department of Education)
• Join DaSy’s Part C Data Manager Community of Practice on the second and fourth Tuesday of every month from 2:00 PM to 2:30 PM ET / 1:00 PM to 1:30 PM CT / 11:00 AM to 11:30 AM PT.
• Contact your DaSy liaison for more information and to get connected.

About the Authors

Tony Ruggiero is an educational analyst at AEM Corporation. He has 27 years of experience in the public, nonprofit, and private sectors in data management and collection, reporting, and analysis in early intervention, education, and health. Tony is a member of DaSy workgroups that focus on child and family outcomes, data standardization, data processes, and the data manager community.

Leah Piatt is an experienced data systems leader with a wide background in education data. She has worked closely with cross-functional teams of state, federal, and contractual partners to produce data exchanges with data visualization layers, focusing on structure, integrity, and data governance policy. She specializes in developing business process improvements, implementing strategic plans and IT roadmaps, and creating process efficiencies within continuous improvement initiatives.

Footnote
¹Redman, T. (2013, December). Getting in front of data quality [Webinar]. Harvard Business Review.

Published June 13, 2025.