A proposal for the systematic assessment of data quality indicators in birth defects surveillance.
BACKGROUND
Quality control and improvement are a key part of the implementation of an effective surveillance program. Data quality indicators (DQI) are key tools but have not been widely used, especially in a low-resource setting.


METHODS
We developed a list of data quality indicators of birth defects surveillance. These DQI address ascertainment, description, coding, and classification.


RESULTS
We developed 40 DQI that can be used widely to assess the quality of data relative to birth defects of major clinical and public health impact.


CONCLUSIONS
DQI have to be both comprehensive (e.g., assess all main surveillance processes) and practical (not require sophisticated or costly data elements), so that they can be used effectively in many different settings. We propose this list of DQI for use in surveillance program as a way to document the quality of the program; detect variations within and between programs, and support quality improvements.
['Groisman|Boris|B|0000-0001-6263-2562', 'Mastroiacovo|Pierpaolo|P|0000-0002-8318-8664', 'Barbero|Pablo|P|0000-0002-6026-744X', 'Bidondo|María Paz|MP|0000-0002-4792-4775', 'Liascovich|Rosa|R|0000-0002-7953-3197', 'Botto|Lorenzo D|LD|0000-0002-5322-7116']
D001118:Argentina D000013:Congenital Abnormalities D000068598:Data Accuracy D003625:Data Collection D006801:Humans D011159:Population Surveillance D019984:Quality Indicators, Health Care
data quality birth defects surveillance