Tagnos uses state of the art AI and Machine Learning algorithms to process signals from hospital operations from various service lines. These predictions help hospitals improve patient flow and increase throughput in various departments.

Our analytics engine can ingest data from any real-time location system (RTLS) solution that tracks the locations of patients, staff members and physical assets. In addition, Tagnos incorporates data from electronic health records (EHRs), computerized physician order entry (CPOE) systems, laboratory and radiology information systems, bed management systems and hospital admission-discharge-transfer (ADT) systems. The solution analyzes all of this data to improve patient flow and to prevent bottlenecks by alerting staff about anticipated problems. The insights generated by the platform are also used to reengineer work flows so that care teams can deliver care more efficiently. 

Tagnos’s analytics engine, which uses AI to identify patterns in large volumes of disparate data, can facilitate a wide variety of logistical tasks. For example, it can predict the start and end times of a surgical procedure. This forecast is based on factors such as the availability of the necessary personnel and supplies, the other procedures that are being performed in the hospital, the acuity of the case, and the average length of time it takes the scheduled surgeon to perform that kind of operation. By alerting turn teams ahead of the time when a case is expected to end, Tagnos ensures that patients will be moved quickly into the recovery area, allowing the next procedure to start sooner.

Tagnos gives hospital administrators visibility into workflow patterns, enabling them to optimize staff utilization and reduce cycle time. This decreased cycle time results in shorter patient waits and improves throughput. Especially in operating rooms and emergency departments, better throughput can translate into additional revenue and ROI. Moreover, the Tagnos solution increases patient satisfaction by keeping patients and their loved ones informed about the status of their care at every step.

The Tagnos solutions include:

OR – Prediction of case times

OR – Prediction of start and end times
Labs – Predict the load on labs
Radiology – Predict load on various service lines in radiology
ER – Predict loads and staff requirements
Assets – Predict where and when equipment is needed