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Big data simulations for capacity improvement in a general ophthalmology clinic.

Christoph KernAndré KönigDun Jack FuBenedikt SchwormArmin WolfSiegfried PriglingerKarsten U Kortuem
Published in: Graefe's archive for clinical and experimental ophthalmology = Albrecht von Graefes Archiv fur klinische und experimentelle Ophthalmologie (2021)
By implementing a big data simulation model, we have achieved a cost-neutral reduction of the mean TWT by 21%. Big data simulation enables users to evaluate variations to an existing system before implementation into clinical practice. Various models for improving patient flow or reducing capacity loads can be evaluated cost-effectively.
Keyphrases
  • big data
  • artificial intelligence
  • machine learning
  • clinical practice
  • primary care
  • quality improvement
  • healthcare
  • deep learning
  • case report