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Postoperative patients are predisposed to episodes of respiratory depression, which if not detected and treated can lead to apnea, anoxic brain injury, cardiac arrest, and death. By continuously monitoring the patient’s end-tidal carbon dioxide (EtCO2), respiratory rate (RR) and fractional inspired CO2 (FiCO2) through capnography, clinicians can more accurately assess ventilation adequacy and predict the onset of declining cardiovascular and respiratory conditions.

Edge computing allows you to create a secure “mini network” of a patient’s bedside medical devices, separate from the hospital’s main network. The edge computing device provides added security by controlling data exchange at the application level, rather than the network level.

Medical devices – especially connected ones – help with identifying and predicting patient deterioration. The insights they provide need to be readily accessible at the point of care and at the moment of care. These are some of the benefits edge computing delivers.

In a survey of healthcare information security professionals taken before the pandemic, a majority of respondents acknowledged that their organizations experienced a significant security incident.

Supporting current clinicians and preventing adverse events throughout the hospital are possible with an enhanced clinical surveillance strategy that involves new data-driven workflows. Enhanced real-time clinical surveillance goes beyond standard monitoring of physiologic parameters to help detect emergent clinically actionable events.

The ability to predict a patient’s clinical deterioration and intervene before an adverse health event occurs – even saving a life – is the ultimate goal for any clinical surveillance strategy.