KEYWORDS:
Immunization Registry, Data Quality, Providers

BACKGROUND:
Since 1998, Partners in Health Systems has managed and maintained regional registries across Upstate New York. As registries integrate into provider practices, examination of the quality of data being sent to the central registry is exceedingly critical. Additionally, it is necessary providers take “ownership” of the data that they use and send to the registry. Therefore our approach to data quality is twofold, one at the registry and another at the provider. Challenges have been encountered in the development of this examination, much of which stems from multiple methods of data being entered into the registry, conversions from former registries, and human error.

OBJECTIVE:
Develop an ongoing process to ensure maximal data quality at the provider site and regional registries.

METHOD:
A data quality team was put together to regularly discuss methods, types of analysis and necessary corrections. Assistance was gained from clinicians, software engineers, local and regional health department staff and many others to ensure the most comprehensive and thorough examination would be undertaken. Using a variety of tools, such as SQL queries, data analysis and audits, the team examines data at the provider level and data sent to the registry.

RESULT:
Scans were created to run monthly for review by the data quality team. Critical scans were identified and designed that could be added to the registry application in the provider offices. Thus allowing the provider site to have the ability to run checks on their own data before it gets sent to the registry, ultimately establishing “ownership” Problem areas involving human error and data loads were identified as the majority of the issues and corrective actions were applied to fix the errors.

CONCLUSION:
Data quality is an integral part of immunization registries, and for registries to succeed data quality practices must be in place to keep the data at its highest level. Ongoing reviews at the provider sites and the data quality team will help ensure this.

LEARNING OBJECTIVES:
To share tools that can be implemented to help maintain data quality audits.