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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.

Function

Benefits

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

Industry

Healthcare

Healthcare Providers And Services

Data Sets

Structured / Semi-structured

AI Technologies

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

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