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With robotic volumes flat for nearly 18 months, this health system was looking for a way to grow volumes and maximize capacity of their existing assets.
The health system lacked visibility into their resource utilization and needed to uncover hidden opportunities to expand access to minimally invasive care for their community.
In just two months, the health system saw a 15% year-over-year increase in robotic surgical volume, as well as service line growth in key areas – a 23% increase in General Surgery and 8.7% increase in OBGYN.
This growth was achieved with their existing robotic systems, demonstrating that there was high demand in their community. This success prompted the health system to invest in new robotics, having gained confidence in the existing and future demand and their ability to fill open robotic time.
Capacity Assistant:
Proactively engages surgeons and schedulers to incentivize block release weeks in advance of auto-release. Qventus ML models predict with high confidence which partial or full blocks are unlikely to be used up to a month in advance, and send schedulers timely and actionable emails to release those blocks, ultimately helping to increase their utilization scores. Non-robotic nudges automatically identify and reconcile non-robotic cases in robotic rooms by facilitating moving cases.
Clinic Scheduler Assistant: Surgeons and their schedulers can view relevant robotics OR time in seconds in an intuitive interface, without having to log in to the EHR. Qventus algorithms intelligently predict the wheels-in to wheels-out case length based on the surgeons’ past performance, CLE trends at the surgeon and department level, time of day, and more, allowing the prioritizing and requesting of available surgical slots.
Strategic Marketing Assistant: ML- driven personalization preferentially markets time to strategic growth surgeons to automatically fill white space.
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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