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A proposal for the systematic assessment of data quality indicators in birth defects surveillance.

Boris GroismanPierpaolo MastroiacovoPablo BarberoMaría Paz BidondoRosa LiascovichLorenzo D Botto
Published in: Birth defects research (2019)
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.
Keyphrases
  • quality improvement
  • public health
  • electronic health record
  • pregnant women
  • artificial intelligence