New Research: How healthcare CIOs are shaping AI’s role in patient care and operations
The AMC needed to address inefficiencies in patient flow, especially discharge planning, to reduce length of stay (LOS) and create more inpatient bed capacity. They did not have a standard discharge planning process across their hospitals, and previous attempts at reducing LOS relied on utilizing a labor-intensive, manual spreadsheet, which had poor engagement from staff.
This health system selected the Qventus Inpatient Capacity Solution to achieve three key goals: drive down excess days, predict and address avoidable discharge delays in real-time, and reduce the burden on care teams.
The Inpatient Capacity solution is embedded directly into the Cerner EHR as an Mpage, making it easy for care team to use it in their existing workflows.
Discharge Planning Assistant: Machine learning models, locally trained on the health system’s patients and care patterns, auto-populate estimated discharge dates (EDD) and dispositions directly into the EHR on the first morning after admission. These models continue to pressure-test the discharge plan, identifying opportunities for earlier discharge and to lower levels of care.
Care Gap Assistant: Identifies and orchestrates the closure of potential gaps in each care plan, including tracking patient-specific milestones. This allows care teams to predict discharge barriers, set milestones in an optimal order, and avoid delays and last-minute scrambles.
Capacity Intelligence Assistant: Accelerates patient flow by identifying in real-time the key actions needed to achieve discharge success, enabling health systems to easily identify and deploy the right staff, allocate resources effectively based on up-to-the-minute patient data, and ensure discharge success.
Simplifying surgical scheduling: Qventus’ digital booking interface, TimeFinder, enables schedulers to easily find open time slots. The software determines the best-fit slots for any given case—factoring in things like day of week, time, the type of room and any special equipment needed, duration of procedure, and more—and offers a list of available slots that most closely fit the criteria. The clinic scheduler can book the time and submit the case request information with just a few clicks.
Improving block time utilization: Machine learning algorithms learn from a surgeon’s historical practice patterns and use that data to predict, up to a month in advance, time within each surgeon’s block that is unlikely to be used. When the system identifies a slot with a significantly high probability of going unused, it sends an automated “nudge” to the surgeon’s scheduler, requesting a release of the slot. To incentivize the release, the nudge includes a calculation of how much the release will improve the surgeon’s block utilization rate.
Proactively filling unused slots: Under a manual process, unused slots are often filled with the first available procedure, rather than the most appropriate one. The Qventus Perioperative Solution’s Available Time Outreach functionality analyzes the characteristics of available slots, matches them with surgeons’ predicted needs, then offers the best-fit slots via email to the surgeon who’s most likely to use it and who also represents the highest value to Banner Health. The scheduler can accept or decline with a few clicks. If they decline, the system automatically moves to the next most likely candidate.
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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.
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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