- Home
- About AIRA
- Workgroups
- Ongoing Efforts
- Events
- Repository
- Members Only
Data at RestBackgroundData at Rest (DAR) is the measurement of data residing in the immunization information system (IIS) database regardless of how it arrived there. This content area puts into practice data quality indicators found in the IIS Data Quality Practices – To Monitor and Evaluate Data at Rest (May 2018). The Measurement and Improvement (M&I) Initiative measures DAR within two different stages using the following indicators:
The concepts measured are defined as: Completeness: The degree to which full information about a data set, record, or individual data element is captured in the IIS (i.e., the proportion of stored data with complete information measured against the potential of “100%”). Validity: The degree to which the data conform to the syntax (format, type, range) of their definitions (i.e., to the rules of what is accepted or expected by the IIS). Timeliness: The amount of time between the occurrence of the real-world event and its documentation in the IIS (i.e., the time lag between the date of vaccination or birth and the date the record is fully processed and ready to use in the IIS). More information on the indicators and concepts can be found in Measures and Tests for Assessment: Data at Rest. Participation in DARThe measurement process and IIS level of involvement for the DAR content area differs from other M&I content areas in three key ways:
As with all other content areas in M&I, participation is voluntary but strongly encouraged for all IIS. IIS and immunization programs interested in participating are encouraged to review the IIS Participation Guide for Data at Rest one-pager member resource and share with their leadership or other staff. Below are the steps and resources for participating in DAR, which are also outlined in the Data at Rest Participation Checklist. Step One: Project Initiation
Step Two: Data Extraction
Step Three: Data Transformation
Step Four: Data Loading
Step Five: Data Analysis
Step Six: Data Quality Improvement
Additional Resources
Updated: 7/30/24 |