The medical industry is on the dawn of a new age where physical devices become commodities and virtual devices become the new standard. This is ushering in a revolution in ICU practices both to better understand an in-patient’s trajectory and optimize control to enable a successful, short, and cost-effective ICU stay.

Of course, by virtual device, I mean algorithms that can process multiple physiology parameters and transform what is measureable into what is meaningful in the context of treatment. ICU treatment decisions are based on physiologic risk, not individual vital signs. The new generation of virtual devices—or algorithms—will allow for continuously learning and improving devices so caregivers can better understand the risks facing individual patients.

Our T3 Visualization & Data Aggregation eliminates the need for hardware-based patient monitoring devices by serving as a virtual machine to aggregate, correlate, and display near real-time patient information. Hospitals securely deploy T3 in their datacenters and feed aggregated patient data to ICU monitors or even to the tablets of ICU caregivers.

This innovative approach allows Etiometry to not only simplify ICU operations by virtualizing patient monitoring, but also to continuously improve patient care without the delays inherent in waiting for improvements to patient monitoring devices.

It also empowers healthcare providers to benefit from big data. We announced in a recent press release that Etiometry has now recorded over 10 million hours of patient monitoring data, effectively providing hospital ICUs with actionable information through data consolidation, enhanced visualization and predictive analytics.

We mine the data to understand how patient disease processes evolve over time so we can continuously improve our analytics. Our Risk Analytics Algorithms combine and continuously convert multiple streams of raw physiological data into near real-time actionable clinical information. By enabling the presentation of patient data in terms of estimated risks to the patient, this approach leverages mechanistic physiology models and a recursive application of Bayes’ Theorem to process various data sources and help caregivers track harmful conditions.

For more information, read our press release that announced that Etiometry has now recorded over 10 million hours of patient data, and check out our blog on the advantages of Deploying Big Data in Hospital ICUs. If you would like to schedule a call to discuss the advantages your hospital can gain by deploying our technology in your ICU, email info@etiometry.com.

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