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Optimizing data visualization for reproductive, maternal, newborn, child health, and nutrition (RMNCH&N) policymaking: data visualization preferences and interpretation capacity among decision-makers in Tanzania.

Tricia AungDebora NiyehaShagihilu ShagihiluRose MpembeniJoyceline KagandaAshley SheffelRebecca Heidkamp
Published in: Global health research and policy (2019)
Decision-makers must be able to understand and interpret RMNCH&N data they receive to be empowered to act. Addressing inadequate data literacy and presentation skills among decision-makers is vital to bridging gaps between evidence and policymaking. It would be beneficial to host basic data literacy and visualization training for RMNCH&N decision-makers at all levels in Tanzania, and to expand skills on developing key messages from visualizations.
Keyphrases
  • electronic health record
  • big data
  • decision making
  • healthcare
  • data analysis
  • health information
  • artificial intelligence
  • case report
  • gestational age