Real-Time Healthcare Analytics: Monitor, Predict, Nudge, Act

October, 2018

It was a Monday night, the busiest time in the ED. The ED charge nurse received an alert on her Vocera smartphone app.

The alert was from Qventus, which predicts operational bottlenecks and recommends course corrections.

The alert was telling the charge nurse that the ED was going to have a surge of patients in two hours. Qventus predicted this with machine learning based on the current census in the ED, historical admit and discharge times, the practice patterns of the clinicians currently working in the ED, and the current queue and expected turnaround times for diagnostic tests.

The alert was delivered through the Vocera Platform, which knew who the on-duty charge nurse was, what device to contact her on, and whom to escalate the alert to if she was not available for some reason.

The course-correction alert advised the charge nurse to work with the transport, lab, and radiology teams to expedite the flow of patients through the ED and ensure beds would be available for the anticipated surge.

The charge nurse sprang into action.

She used Vocera communication software to connect and communicate instantly and directly with the teams in each area. All she had to do was say the name, function, or group name she wanted to reach. She didn’t even have to search for people in a directory.

She mobilized the transport teams to start moving patients who were ready to be admitted to inpatient beds. This freed up beds in the ED.

She contacted the teams in lab and radiology to prioritize tests for patients in the ED who were waiting. Equipped with those test results, the ED team expedited processing of waiting patients. This freed up more beds in the ED.

The charge nurse never had to go back to the nurses’ station to accomplish any of this workflow. She did it all while entirely mobile.

Two hours later when a wave of patients flowed in, the ED team was prepared. Beds were available. The charge nurse was grateful. And the patients were, too.

Predicting Potential Issues and Delivering Course Corrections to the Right People

This hospital integrated their Qventus solution with the Vocera Platform, combining powerful AI capabilities from Qventus with communication capabilities from Vocera.

Qventus uses decision science and machine learning to continuously monitor a hospital’s operational data, predict potential issues, and deliver recommended course corrections or “nudges.”

When a hospital integrates Qventus with Vocera, Qventus nudges are sent through the Vocera Platform as prioritized, actionable notifications. These notifications are delivered to the appropriate frontline staff on their mobile devices, including the wearable Vocera Badge and the Collaboration Suite smartphone app. Frontline staff can then mobilize the right resources instantly and directly, with closed-loop communication.

Frontline staff receive these important course corrections in the same communication system they use for receiving other clinical alerts and alarms, voice communications, and secure texting. The Vocera Platform provides a unified user experience for all clinical communications and workflow.

Qventus is one of more than 150 clinical and operational systems from which the Vocera Platform can integrate and combine data. The platform also has comprehensive master directory of care team data, which it can integrate from multiple sources like EHR and nurse call systems. The platform knows the current presence and availability of care team members and can determine the appropriate notification workflows. This is what allows  Qventus nudges to be sent to the right people, at the right priority level, with the right context, and the right escalation path.

Improving Patient Flow in the ED, Inpatient, and OR  Units

Three areas in which operational bottlenecks often occur in hospitals are the ED, inpatient, and OR units. Typically, the data to efficiently run these centers exists in a hospital’s EHR and other systems. But Qventus harnesses it into meaningful and actionable information that is usually impossible for leaders to analyze in the moment.

Predicting ED Surges to Help Streamline Patient Throughput

Up to 70% of a hospital’s admissions come through the ED. When the ED is overwhelmed, admitted patients are boarded there while the staff scrambles to clear beds by discharging patients. Faced with long wait times, some patients leave before being seen or before completing treatment. Inpatient units cannot turn around beds fast enough to accommodate so many new patients.

Qventus predicts ED surges, how many patients will leave without being seen, how many will require admission, and more. Through the Vocera Platform, Qventus nudges are delivered through to the right people in the moment.

Surfacing Discharge Barriers and Capacity Bottlenecks in Inpatient Units

When patients stay in the hospital longer than they should, capacity becomes constrained across the hospital. This can impact quality of care and hospital margins. Sustainably reducing length of stay and excess days has been particularly difficult because of the challenges of coordinating across multiple teams within a highly dynamic, highly variable environment.

Key workflows such as discharge planning, capacity management, and ancillary coordination are inconsistent and highly reactive. Patients waiting to be discharged can be held up by barriers that could have been resolved earlier in the patient stay.

Qventus helps inpatient units manage length of stay by intelligently surfacing anticipated discharge barriers and capacity bottlenecks. The predictions are delivered via a nudge to the frontline staff. The nudges fit seamlessly into same communication flow teams are using to coordinate care across clinical and ancillary departments.

Teams can mobilize in preparation for predicted discharge barriers and prioritize patients at risk for avoidable days. They can more effectively and consistently plan for discharge early in the patient’s stay and facilitate proactive capacity management.

Improving Predictability and Optimizing Utilization of the OR

The OR is a key profit center for hospitals and is also a high-cost fixed asset. Uncoordinated teams, schedule changes, and late starts force staff to react as the day unfolds.

Qventus helps ORs streamline patient flow from pre-op through post-op care, optimize block utilization, and improve staffing and supply cost management. With machine learning, the solution predicts case delays, prioritizes room turnarounds, improves timely block release, and helps post-op teams anticipate patients. This helps ORs improve predictability and optimize utilization.

Sending proactive nudges to staff on the voice-driven, hands-free Vocera Badge allows perioperative teams to coordinate care even when scrubbed in or working with patients and sterile equipment. And the Vocera broadcast capability ensures the right team members are hearing the same message at the same time.

The Best of What Two Leaders Have to Offer

A Qventus-Vocera solution brings together decision science, behavior science, and machine learning from Qventus with clinical communication and collaboration software from Vocera. The value of Qventus to predict and prescribe is enhanced when combined with intelligent, multivariate rule-driven, and role-based workflows from Vocera.

Together the combined solution helps improve patient care, safety, and experience, and foster caregiver resiliency.

Click here to get the solution brief, Real-Time Operations Management Solution Powered by Qventus and Vocera, and/or to contact Vocera.