Abstract
A literature review of data quality issues highlights how the quality of health data has been discussed in the biosurveillance literature and frames it in relation to the broader data quality (DQ) field. Results of the literature review include: completeness as the most commonly measured dimension of DQ; methods for regular DQ monitoring and occasional evaluation; various methods of improving data quality; and communication with the data entry personnel as the most common preventative step. The results suggest that developing a DQ program could facilitate understanding the sources of poor DQ; recognizing DQ problems; and improving DQ for improved efficiency and effectiveness of biosurveillance systems.