We use Conventional analytics is based on threshold-based alerts that categorize severity of various symptoms monitored by imedic devices into high-, medium, and low-priority.


With cutting-edge innovation, and devices RPM has allowed care to be delivered and effectively treat patients. Imedic software solutions are utilized for deep analytics and easier workflow integration.

Conventional analytics rely on threshold-based alerts that categorize the severity of the heart failure symptoms into high, medium and low-priority. In conventional analytics, we classify only the high-priority alerts as 'positive' and other types of alerts as 'negative'. The RMS device can generate multiple alerts in a day. Multiple alerts may be a result of taking multiple measurements of the same vital signs.

In either case, only a single intervention is conducted by the call center nurses in responding to all the alerts generated for a patient on a particular day. Therefore, in the analysis, we aggregate all alerts of the same patient on any given day and consider only the highest priority alert, and discarding the remaining ones. We denote a prediction made on each day as a single-day prediction.

Healthcare providers gather crucial patient information to use predictive analytics to make care more accurate and patient-centric by using imedic software solutions and RPM devices.