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AI Use Case

Predict individual hospital admission rates using historical and real-time data

Predict individual hospital admission rates using historical and real-time data. The output will hemp both individuals and institions affected but also overall capacity planning across medical organisations.



Operational - Enables Just in Time approach,Operational Support - Demand forecasting,Cost - Optimise resource allocation

Case Studies

MetroHealth~MetroHealth predicts patient flow to improve operational decision making using machine learning ,Natividad Medical Center~Natividad Medical Center reduces time to see doctor by 20% and left without being seen rates by 42% by optimising patient flow and resource allocation in ER,Johns Hopkins Hospital~Johns Hopkins Hospital improves patient monitoring and resource allocation in ER and critical care units in real-time using machine learning,Mercy Hospital Fort Smith~Mercy Hospital Fort Smith improves patient flow and throughput in the ER to improves LWBS rates by over 30% using machine learning,University College London Hospitals~UCLH plans to use machine learning to triage patients in A&E and better predict demand for the service,"""The George Institute for Global Health, Oxford University""~Researchers at the George Institute for Global Health improve emergency room admittance predictive models using machine learning"

Potential Vendors

Qventus,Qventus,GE Healthcare,Qventus,Alan Turing Institute



Healthcare Providers And Services

Data Sets

Structured / Semi-structured

AI Technologies

Machine Learning (ML),ML Task - Prediction - Regression

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