Data Quality Workgroup - Data ReportingBuilding upon the earlier work of the Data Quality Action Team, the Division of Program Statistics (DPS) and the Office of Information Technology (OIT) identified CHS reporting problems in the (OIT) national data repositories that adversely effect the production of workload data, and have the potential to adversely effect the production of user population data. Both sets of information are used to determine Area and Tribal fund allocation. Since the problem is one of duplication of encounters, rather than omission, it is not expected that the effect on user populations will be large. However, since the Agency (e.g., Division of Facilities Planning and Construction) is dependent on accurate CHS workload data, and because the IHS National Data Warehouse will begin loading CHS data (and other data) within the next six months, it is important to address these problems immediately. A national-level CHS Data Quality Work Group was formed in April of 2003 to investigate and resolve CHS problems in the data repositories.
Over the course of the project, the workgroup explored methods to improve CHS data reporting quality through a focused analysis of current practices, participation in information technology training, and documentation of key data processes. A team of 21 experts in CHS and information technology systems worked together to analyze the existing data repository issues such as metadata, inconsistent data elements, inconsistent "encounter" definitions, and CHS data validation.
This document presents concise documentation of the following processes:
- business definitions, data movement, and data export;
- data extract, transformation, load processes and unduplication processes in the national data repositories;
- local and national reporting practices; and recommend new local and national reports that will meet the needs for validation of data in the repositories.
The final workgroup report contains full technical documentation of the issues and recommendations for short- and long-term goals and strategies for the improvement of CHS data quality.