How AI-driven OR scheduling drives growth and reduces staff frustration at Abbott Northwestern

Inefficient manual scheduling processes feed a vicious cycle of surgeons holding unneeded block time that leads to a perception of lack of OR availability and underutilization.

Through AI-based solutions, health systems can break this cycle, reduce surgeon frustration and unlock OR growth.

In a January Becker's Hospital Review webinar sponsored by Qventus, Whitney Johnson, director of surgical services at Minneapolis-headquartered Allina Health, and Derek Fine, senior customer success manager at Qventus, discussed how manual processes fuel scheduling problems and how AI-driven solutions helped Allina Health's Abbott Northwestern Hospital in Minneapolis release OR time and support more strategic use of that time. 

Four key takeaways were:

  1. Manual OR scheduling processes contribute to staff burnout and hamper growth. Many health systems still rely on manual processes to assign surgeons to operating rooms, which leads to inconsistent and error-prone scheduling. It often means that surgeons cannot get the rooms they need when they need them or are assigned expensive robotics rooms for non-robotic cases.

Allina Health struggled with these and other challenges. "We are currently focused on right-sizing our staff based on the migration of cases to our community ambulatory surgery centers," Ms. Johnson said. "We also need to think strategically about how we differentiate ourselves in a competitive market." 

  1. By using machine learning, health systems can increase available OR time by predicting specific block times that are unlikely to be used. "The first step in optimizing access is through block release," Mr. Fine said. "You need to unlock as much time as possible on the schedule as far out as possible, and you have to do that without frustrating your surgeons."

The Qventus solution uses AI to predict which blocks are likely to be unused more than 30 days in advance. By using behavioral science, the solution engages surgeons and incentivizes proactive release. "We show them the probability behind the prediction, which builds confidence and trust, as well as how much their block utilization will benefit if they release the block prior to the manual release cut off, which helps incentivize desired behavior. And we try to make this process as simple as possible," Mr. Fine said.

By using Qventus, Abbott Northwestern successfully increased its surgical case volume by 3.6 cases per month per operating room. "In the last three months, we've had 269 hours of OR block time released early via this auto-nudge process, of which 49 percent was then later utilized, resulting in 132 hours of additional OR time filled," Ms. Johnson said.

  1. AI optimizes the use of robotic operating rooms, supporting a growth in robotic capacity. The Qventus solution frees robotic capacity by detecting non-robotic activity in robotic rooms, automatically offering an alternative OR time to that surgeon and then advertising open robotic time to strategic surgeons. 

"At Abbott Northwestern, our most motivated surgeons, by far, were those frustrated with the robotic scheduling access," Ms. Johnson said. "Surgeons were booking out much further than we would want them to, resulting in poor utilization. By bringing transparency to surgeons looking for open time, we drove significant increases in overall robotic volume and utilization, increasing productivity per robot by 42 percent." Since go-live, the hospital has doubled the number of robots. "We really could not have been able to justify the additional robots without solving our scheduling and robot utilization challenges."

  1. By personalizing outreach to surgeons using machine learning, Qventus reduces often ignored notifications, and it drives strategic growth. The solution predicts the best-fit surgeon based on practice patterns, past performance and strategic goals, offering priority OR time when they are most likely to want it. "Qventus reaches out to surgeons with personalized  updates about times in the schedule they could use, which are in line with the system's strategic goals," Mr. Fine said. "That removes the burden from the scheduler to manually reach out."

For Abbott Northwestern, this has resulted in an average of 30 additional cases per month in the last two months alone added through machine learning-driven automated outreach. "It has been really helpful as we work toward meeting our volume targets," Ms. Johnson said. "Not only are these results positive from a financial perspective, but automated outreach has created goodwill with our surgeons and allowed us to prioritize our most important clinical service lines."

For Abbott Northwestern, Qventus has helped the health system meet its volume goals, reignite growth and reduce staff burden. With 98 percent of OR requests accepted and a 24-minute average turnaround to find OR time, the system has reduced manual work and vastly improved scheduling efficiency.

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