Effective clinical and public health practice in the twenty-first century requires access to data from an increasing array of information systems. However, the quality of data in these systems can be poor or âunfit for use.â Therefore measuring and monitoring data quality is an essential activity for clinical and public health professionals as well as researchers. Current methods for examining data quality largely rely on manual queries and processes conducted by epidemiologists. Better, automated tools for examining data quality are desired by the surveillance community.
To extend an open source analytics and visualization platform for measuring the quality of electronic health data transmitted to syndromic surveillance systems.