Data Quality

Overview

Data Quality icon

Part C and Part B 619 programs rely on data to inform decisions on program improvement, track child and family progress, and report performance to federal, state, and local policymakers and other stakeholders. Using inaccurate or poor quality data to report on program performance or make decisions will result in erroneous conclusions. Therefore, it is necessary to have comprehensive policies and procedures to ensure high-quality data—data that are accurate, consistent, timely, and complete.
The importance of data quality is addressed by the U.S. Department of Education’s Implementing Regulations for Part C programs as follows: “Each statewide system must include a system for compiling and reporting timely and accurate data…” (34 CFR 303.124(a)). In addition, Part C regulations at 303.723 require the lead agency to submit a certification signed by an authorized official of the agency that the information provided, “is an accurate and unduplicated count of infants and toddlers with disabilities receiving early intervention services.” These regulations require that data quality be a high priority for Part C and Part B 619 programs.

Definition
Data Quality: A multi-dimensional measurement of the adequacy of a particular datum or data sets based on a number of dimensions including, but not limited to accuracy, completeness, consistency, and timeliness.
Source: BusinessIntelligence.com.

A comprehensive approach to data quality involves the intersection of people, processes and data system(s).

People (roles/responsibilities): Individuals at the state or local level who collect, enter, prepare, analyze, report, and/or access data are responsible for ensuring that the data are and remain of high quality. Policies should communicate role expectations, outline data quality monitoring responsibilities, and prepare for staff transfer of knowledge when there is staff turnover. It is important that data governance policies for data quality include training and professional development opportunities for anyone who collects, maintains, or uses Part C or Part B 619 data.

Processes: Part C and Part B 619 programs need to have clearly documented and consistently applied processes and procedures to support data quality through summarizing, analyzing, and reporting of data. Included in data quality processes should be regularly updated documentation (data entry manuals, data dictionaries, tip sheets), continuous data quality monitoring and checks/audits, and procedures for correcting data quality issues when discovered.

Data system(s): Data systems used by Part C or Part B 619 programs should have the capability to perform automated edit checks to reduce data entry errors (e.g., such as having predefined option sets, acceptable response ranges, etc.). That is, when a person is entering data, the data system automatically identifies data entry values that are questionable so they can be confirmed or corrected as soon as possible. The system should generate reports at all levels (child record, provider, agency, etc.) to help identify potential data errors.

Data governance policies that address data quality must clearly communicate expectations for how data are to be collected, entered, prepared, analyzed, and reported. For effectiveness, data quality policies should specify responsibilities for specific data quality actions, the processes associated with these actions including timelines, and how the data system contributes to data quality.

Part C and Part B 619 programs operate within the state agency in which they are housed. Thus, the structure and content of any data governance already within an agency is of particular importance. Before developing any data quality policy, Part C and Part B 619 programs should review policies regarding data quality developed by the agency in which their program resides. Existing policies might need to be updated with specific references or provisions related to Part C or Part B 619, in which case the considerations and the template below may be helpful in proposing language for this purpose.
Where no policy on data quality exists or a separate policy related to Part C or Part B 619 is needed, the template following the Considerations section is fully editable and prepopulated with language to expedite writing new data quality policies.

The DaSy Data System Framework emphasizes the importance of data quality in the Data Governance section, Quality Indicator DG4 & DG5, in the System Design and Development section, Quality Indicator SD4, and in the Data Use section, Quality Indicator DU2.

Considerations

Use the questions below to discuss, consider, and develop a comprehensive data quality policy. Where appropriate, procedures and operational manuals that detail specific actions supporting implementation of this policy should be created.

1. Data Quality Policy: General Provisions

  1. Which federal laws/regulations (IDEA/FERPA) related to data quality apply to your Part C or Part B 619 program?
  2. Are there additional state agency policies related to data quality that apply to the Part C or Part B 619 program? If yes, what are they?
  3. What specific Part C or Part B 619 data quality policies or procedures, if any, exist and apply?
  4. Which role, within what agency/program should be contacted with questions about this policy?
  5. Which role, within what agency/program is responsible for ensuring adherence to this policy?
  6. Which role, within what agency/program is responsible for monitoring adherence to this policy, and how will the monitoring be conducted?
  7. Which role, within what agency/program is responsible for managing the implementation of this policy including provision of training and technical assistance?
  8. What consequences, if any, will apply when this policy is not followed?
  9. How often will this policy be reviewed for necessary revisions?
  10. How will the public be informed about this policy? Where will it be posted on the state’s website?

2. Data Quality Policy: Responsibility

  1. Which role, within what agency/program is responsible for overseeing and monitoring data quality for the overall data system and for particular data collections?
  2. What participating agencies, if any, will be required to follow this policy and under what mechanisms (e.g., contracts, subgrants, or interagency agreements)?
  3. Which role, within what agency/program develops and revises data quality policies and procedures/manuals?
  4. Which role, within what agency/program is responsible for creating and reviewing Part C or Part B 619 data reports to determine whether data are of acceptable quality?
  5. Which role, within what agency/program is responsible for responding to end users’ data quality questions?
  6. Which role, within what agency/program is responsible for correcting data quality issues once data quality problems/issues have been identified or reported?
  7. Which role, within what agency/program is responsible for communicating about data quality issues/problems to data governance group(s), local programs and stakeholders?
  8. Which role, within what agency/program is responsible for ensuring adherence to data quality procedures when data are exchanged or transferred?
  9. Which role, within what agency/program is responsible for training/retraining staff on the importance of data quality and how to identify data quality issues/problems? What content is delivered at trainings and how are they conducted?

3. Data Quality Policy: Processes

  1. What processes/procedures are in place to ensure that data are accurate, consistent, timely, and complete?
  2. What documentation exists that details how data are collected and entered into the data system (e.g., data entry manuals, data dictionaries, tip sheets)?
  3. What kinds of regular data quality checks/audits are completed by Part C and/or Part B 619 staff? How often is each check completed?
  4. What mechanism is in place for end users to report data quality issues/problems?
  5. How are data quality issues resolved/corrected?
  6. If data quality issues/problems are identified, what process is in place to prevent future data quality issues/problems (e.g., training/retraining of staff, changes to the data system, document updates)?
  7. How are data quality issues communicated to local programs and stakeholders?
  8. How often are data quality policies reviewed and updated?
  9. What process is used to obtain input from users and other stakeholders when reviewing and revising data quality policies?

4. Data Quality Policy: Data System(s)

  1. What automatic edit checks are built into the data system(s) to help ensure data are entered accurately (e.g., predefined option sets, field definitions, out-of-range checks, error messages)?
  2. What reports in the data system(s) are used and/or needed to help identify outliers, data anomalies, errors, or inconsistencies?
  3. How is input (reviews, testing, feedback) obtained from users as revisions are considered in system edit checks or reports that detect data quality issues?

Data Quality Policy Template

Use, and modify as needed, the template linked below for developing a data quality policy. Select the highlighted text and replace with your state/program information. We recommend that you consult with relevant staff and stakeholders when developing these policies. Upon completing the template, be sure to follow your state’s processes for finalizing and enacting policy.

Download Template for Data Governance Data Quality Policy