Shaping a Vision for 21st Century Health Statistics. Data quality issues


Data quality suffers now because of the lack of standardized terminology, definitions, concepts, transmission formats, analysis, and dissemination. The multiplicity of today’s data sources makes it necessary to pay close attention to the quality of each source and its specific limits and capabilities. Ensuring future data quality will involve improving the quality of records through technology and education of data providers. For example, technology can contribute to improved quality by permitting automatic querying while data are being collected, rather than afterwards when incompleteness and inaccuracy are more difficult to correct. In addition, surveys need to be improved by investment in survey research, cognitive research, and evaluation.