Monday, October 27, 2003 - 2:00 PM
3904

This presentation is part of A2: Development and Implementation of Data Quality Monitoring Processes

Improving data quality with electronic processes

Christopher G Pratt and Sandra Schulthies. USIIS Program, Utah State Dept. of Health, PO Box 142001, Salt Lake City, UT, USA


KEYWORDS:
Data quality, data matching, electronic data processing

BACKGROUND:
During the year of 2002, manual methods for improving data quality in the Utah State-Wide Immunization Registry (USIIS) were not able to keep up with the quantity of data to be reviewed. In order to prevent the continuation of this trend, improvement of existing electronic processes and the implementation of new processes are being utilized as a means of reversing this observation.

OBJECTIVE:
Present USIIS’ experience of what has worked and not worked in regards to the electronic processes it has implemented for the management of data quality.

METHOD:
Measurements in the spring of 2003 showed the number of records to be manually reviewed were growing at a rate of approximately 3,000 per month. Improvements of existing electronic matching procedures are underway to reduce the number of records needing to be manually reviewed. Duplication rates in the USIIS registry are estimated at between 8% and 25%, with the actual rate probably close to 12%. A product called LinkSolv is being used to more accurately determine this figure and will also be used to measure improvements achieved with the various solution approaches.

RESULT:
Final results have not yet been determined. Results, both good and bad, on all strategies will be presented at the time of the conference.

CONCLUSION:
It is our assumption that through the utilization of electronic methods, data quality can be improved. Other registries are facing or will face data quality issues and the approaches and experiences of USIIS may help other registries make more informed decisions when this issue is confronted.

LEARNING OBJECTIVES:
Attendees will have a better understanding of the data quality issues that registries have and possible solutions to these problems.

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