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