Data Quality

Description: 

Problem Summary

Data collection across a growing stream of contributing facilities and variables requires automated, consistent, and efficient monitoring of quality. Epidemiologists tasked with analyzing syndromic data need to be confident in the overall quality of their data, and aware of the effects of poor data quality when interpreting data. Data quality is also increasingly important as data are shared across jurisdictions and combined for analysis.

Original Publication Year: 
2017
Event/Publication Date: 
October, 2017

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INTERNATIONAL SOCIETY FOR
DISEASE SURVEILLANCE

288 Grove Street, Box 203
Braintree, MA 02184
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Email:syndromic@syndromic.org

This Knowledge Repository is made possible through the activities of the Centers for Disease Control and Prevention Cooperative Agreement/Grant #1 NU500E000098-01, National Surveillance Program Community of Practice (NSSP-CoP): Strengthening Health Surveillance Capabilities Nationwide, which is in the interest of public health.