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Home > Systemwide > Information Systems and Data > Improving Data Quality
Improving Data Quality
Organizations must strive to improve the quality of data collected to ensure accurate analyses and reports of services provided to—as well as outcomes for—children, youth, and families. The following resources discuss strategies for improving the collection and use of high-quality data, including State and local examples.
Accountability, Evidence, and the Use of Information Systems in Social Service Programs
Carrilio
Journal of Social Work, 82(2), 2008
View Abstract
Determines that improving workers' skills and comfort levels with data systems and maintaining an open dialogue about how the data will be used may be key components to improving the use of data systems.
Adoption and Foster Care Analysis and Reporting System (AFCARS): State Guide to an AFCARS Assessment Review
Children's Bureau (4th ed.) (2009)
Helps State child welfare program and system staff learn more about the AFCARS Assessment Review process, including information on AFCARS requirements, data element standards, and data collection processes. States may also use the guide as a self-assessment tool.
Client Feedback in Child Welfare Programs: Current Trends and Future Directions
Baker
Children and Youth Services Review, 29(9), 2007
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Considers the problems in methodologies of collecting reliable data and identifies directions for future research in this area, including a discussion of standardized systems and measure validity.
Gaps and Strategies for Improving AI/AN/NA Data: Final Report
Westat (2007)
Reviews the availability and adequacy of Federal and other data sets on the health and well-being of American Indians, Alaska Natives, and other Native Americans, identifies current initiatives to reduce gaps in the data, and presents strategies that may improve data quality.
NDTAC Data Brief: Title I, Part D Data Quality
National Evaluation and Technical Assistance Center for the Education of Children and Youth Who Are Neglected, Delinquent, or At Risk (2007)
Describes States' efforts to improve the quality and integrity of data collected on educational services for youth.
Putting Administrative Data to Work: A Toolkit for State Agencies on Advancing Data Integration and Data Sharing Efforts to Support Sound Policy and Program Development (PDF - 1950 KB)
Child Health and Development Institute of Connecticut (2005)
Provides an assessment tool to help State agencies determine their data and research infrastructure needs and describes guidelines for implementing strategies to improve data quality.
Recommendations for Improving Child Abuse and Neglect Data and Services for American Indian and Alaska Native Children (PDF - 266 KB)
National Indian Child Welfare Association (2008)
Presents policy and research recommendations for developing a mechanism to enable Tribes to participate in a nationwide child abuse and neglect reporting system.
Using Administrative Records to Evaluate the Accuracy of Child Abuse Reports in a National Survey of Child Abuse and Neglect (PDF - 61 KB)
Smith, Biemer, Dowd, & Chiflikyan (2007)
Examines caseworker-provided data about recurring reports (re-reports) of child abuse and neglect, and discusses potential factors involved in data collection that may cause incomplete data.
Using Agency Records
Hatry (2004)
In Handbook of Practical Program Evaluation (2nd ed.)
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Offers strategies for dealing with issues and problems that may arise when using agency records, including missing or incomplete data, changing definitions of data elements, confidentiality and privacy considerations, and more. Also provides data checks for maintaining quality.
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State and local examples
Developing and Implementing Outcomes Training in the Field of Family Support: A Case Example
Reed-Ashcraft, Smithdeal, Kittle, Sharma, & McClune
Professional Development: The International Journal of Continuing Social Work Education, 7(1), 2004
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Describes a program in North Carolina with a goal of improving family support providers' use of a standardized outcomes assessment tool in the field.
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