A Digital Twin platform creates a virtual model that is the exact counterpart (or ‘twin’) of a physical thing – whether that’s an entire hospital, a single patient or an anatomical structure.
Connected data sources like building sensors, staff schedules, electronic health records (EHRs), disease registries, wearable sensors can then be mapped to create a virtual twin.
By enabling the visualisation of data, coloured with context and situational awareness, Olinqua’s Digital Twin capabilities provide invaluable benefits to administrators, engineers, care providers, leadership teams and beyond.
The Olinqua platform bridges the gap between here-and-now actionable events and historical data so that every observable event occurring can be assessed for business meaning and transformed into business outcomes.
AI algorithms are used to analyse the virtual model created to improve a wide variety of common hospital issues, thanks to the increased awareness and oversight that digitisation provides.
Actionable events like bed shortages, spreading of germs, staff schedules, and operating room availability can be predicted and optimised to improve patient care, cut hospital costs, and increase staff performance.
By virtualising a hospital, a Digital Twin can create a safe environment in which to test the influences of changes on system performance – without incurring the same immediate, real world risks.
A Digital Twin is a tool that can help engineers, care providers and administrators to understand how a hospital system is performing right now, while also predicting how it will perform into the future.
Through analysis of the data provided by a wide variety of connected sensors, combined with other pertinent hospital software and systems, Artificial Intelligence can make intelligent predictions with high levels of accuracy that improve operational efficiency as well as patient care outcomes.