Patient status engine combines wireless body-worn sensors with cloud-based electronic health record

May 21, 2012 // By Julien Happich
Isansys Lifecare introduced the Patient Status Engine, a cloud-based wireless sensor vigilance system for real-time and predictive patient status monitoring.

The Patient Status Engine is a complete end-to-end system that integrates wireless body-worn sensors with a cloud-based HIPAA/HL7 compliant Electronic Health Record (EHR), to transform real-time and historical continuous vital sign data into clinical status indicators and prediction tools. With the availability of these new cloud-based indicators and tools, healthcare providers can be notified of any change in a patient's health status as it happens or predict changes that may happen in the future. This can address issues of in-hospital patient safety and avoidable deteriorations and significantly reduce hospital admission times. The Patient Status Engine allows healthcare providers to continue 24/7 surveillance of patients even after they have been discharged from hospital. As a networked and cloud-based system, patients and clinicians may be located anywhere. A further benefit is that a quantified record of a patient’s physiological status is established that can be used for audit purposes or to determine the effectiveness and quality of care.

Last month, Isansys announced CE certification for its LifeTouch Patient Surveillance System, comprising the LifeTouch HRV011 intelligent body-worn wireless sensor and associated Patient Gateway believed to be the world’s first cloud-ready medical device of its kind, and the first to be certified as a Class IIa medical device under the European Medical Device Directive (MDD). Today’s Patient Status Engine launch is the extension of the LifeTouch System into the clinical healthcare cloud. The LifeTouch HRV011 sensor performs a key patient digitisation function within the Patient Status Engine, and together with other devices allows healthcare providers to collect five vital signs continuously, wirelessly and in real-time – Heart Rate (HR), Respiration Rate (RR), Blood Pressure (BP), Pulse Oximetry (SpO2), and Temperature (T). The system also analyses the ECG signals to provide the essential data for Heart Rate Variability (HRV) techniques and methods. Other sensors such as accelerometers, weight scales and blood glucose sensors can be easily added to the network.

The data from the body