CUSTOMER SUCCESS STORY

Creating new bed capacity using Qventus automation

Academic Health System
Boston
Epic EHR
1 facility
THE CHALLENGE

At BMC, operational inefficiency was reaching critical levels

Like many health systems, Boston Medical Center had inefficiencies in their care processes that led to increased costs and impacted quality and experience. They decided to first focus discharge planning improvement efforts on the 10% of length of stay outliers—but they were missing the other 90% of patients.

They desired to drive impact at scale but faced limited resources. Ultimately, to make this successful and scale early discharge planning for as many discharges as possible, they needed to move beyond manual processes and efforts.
QVENTUS DEPLOYMENT

We helped them harness the power of AI and automation

To help BMC achieve their goals, we implemented our industry-leading Inpatient Solution. By automating early discharge planning, our technology helped them improve throughput, reduce excess days, and decrease staff workload.

“This system reduces workload intensity, mitigates process variability, and optimizes our existing staff and resources. We actually feel much stronger today because of this.”

Chris Manasseh, MD
Associate Chief Medical Officer, Inpatient Operations

“Qventus understood the path we needed to take to drive change. We partnered with them because they brought a combination of technology and consultant mindset around change management.”

Alastair Bell, MD, MBA
EVP Strategy & COO

RESULTS

Qventus impact

FTE hours saved
25400
effective bed capacity created
13 beds
of robotic capacity opened annually
1.196 hrs
total days saved with early discharge planning
3200
SOLUTIONS

What we deployed for Boston Medical Center

Qventus Inpatient Capacity Solution

For Multidisciplinary Discharge Rounds (MDRs), Qventus uses AI and machine learning to autopopulate or suggest discharge dates, dispositions, and barriers to discharge to reduce frontline burden and improve discharge planning quality.

The solution triggers automation workflows to make sure ancillaries are prioritizing orders for discharge, and also nudges leadership teams in real time if processes slip. This ensures that by the time the patient is clinically ready for discharge, they are ready to leave the hospital and provides a better experience for their patients and staff.

More about our Inpatient Capacity Solution
SOLUTIONS

What we deployed for Boston Medical Center

Inpatient Solution
FUTURE SOLUTION
FUTURE SOLUTION
FUTURE SOLUTION

Inpatient Solution

For Multidisciplinary Discharge Rounds (MDRs), Qventus uses AI and machine learning to autopopulate or suggest discharge dates, dispositions, and barriers to discharge to reduce frontline burden and improve discharge planning quality.

The solution triggers automation workflows to make sure ancillaries are prioritizing orders for discharge, and also nudges leadership teams in real time if processes slip. This ensures that by the time the patient is clinically ready for discharge, they are ready to leave the hospital and provides a better experience for their patients and staff.

More about Inpatient Solution
A healthcare professional meets with a young female patient at a hospital representing HonorHealth

Future Solution

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Future Solution

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Ut blandit pulvinar volutpat. Cras egestas sem turpis, non accumsan justo cursus viverra. Proin ipsum arcu, dignissim a enim eu, tristique eleifend orci. Etiam commodo dignissim nisi, sed finibus metus auctor in. Nulla venenatis porttitor risus non pretium. In rhoncus tempor mauris. Orci varius natoque penatibus et magnis dis parturient montes, nascetur ridiculus mus.
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A healthcare professional meets with a young female patient at a hospital representing HonorHealth

Future Solution

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Ut blandit pulvinar volutpat. Cras egestas sem turpis, non accumsan justo cursus viverra. Proin ipsum arcu, dignissim a enim eu, tristique eleifend orci. Etiam commodo dignissim nisi, sed finibus metus auctor in. Nulla venenatis porttitor risus non pretium. In rhoncus tempor mauris. Orci varius natoque penatibus et magnis dis parturient montes, nascetur ridiculus mus.
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A healthcare professional meets with a young female patient at a hospital representing HonorHealth
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