Cumbersome manual scheduling processes for operating rooms (ORs) and surgeons' fears of not having enough OR time often lead to hoarding block time, which results in underutilization of the OR and lost revenue.
By using artificial intelligence (AI), machine learning (ML) and automation, perioperative services can identify and incentivize earlier release of block time that can be offered to surgeons with high-margin cases.
In a September Becker's Hospital Review webinar sponsored by Qventus, four perioperative experts discussed key challenges associated with OR scheduling, how automation works in addressing these challenges and the impact and results that AI and ML can have in perioperative services. Panelists were:
- David Atashroo, MD, managing director, perioperative services, Qventus
- Lori Herrman, RN, director of surgical services, Saint Luke's (Kansas City, Mo.)
- Ashley May, surgical services and transplant business operations manager, Saint Luke's (Kansas City, Mo.)
- Mairi McCartney, RN, assistant director of perioperative care services, UAMS Health (Little Rock, Ark.)
Three key takeaways were:
1. Manual processes and tools cause problems for OR teams. Saint Luke's, with 26 operating rooms, and UAMS Medical Center, with 28 operating rooms, face similar challenges:
- Backlog of cases to schedule. "One of the main things we heard from our physicians is that no one was answering the phone when they called to schedule," Ms. McCartney said. The reason was because the three schedulers were always on the phone scheduling. This shows the need for faster, more efficient case scheduling.
- More cases and fewer staff. "Although we have a need for a lot of surgeries and have up to 13 rooms daily, we only have enough staff for 10 rooms," Ms. Herrman said.
- Unpredictability of staff schedules. Unpredictability is due to add-on cases, late-running cases and slow turnover, which leads to missed start and end times.
- Administrative burden. A high volume of back-and-forth phone calls and data entry distracts staff.
- Burnout. Lack of work-life balance results in stress and overwork.
2. Qventus’ software goes beyond manual analytics to automate key OR processes and reduce workload. According to Dr. Atashroo, four elements are required for simplifying operations and driving strategic growth in the fastest, most sustainable way:
- AI & machine learning. Technologies such as AI and ML "are learning models that are operationalized into intuitive interfaces for end users," he said.
- Automation. Tasks like writing data back into the EMR and searching for open capacity can be automated.
- Behavioral science. "This is the 'why' we're asking someone to do something," Dr. Atashroo said. "They need to know what's in it for them; they need to understand that more time is being released and that increasing the level of engagement from surgeons will result."
- Comprehensive data. External real-time market data complements EHR data, providing insights that help drive growth in the areas that hospitals prefer.
3. Saint Luke's and UAMS have realized significant benefits using the Qventus Perioperative Solution. At Saint Luke's, machine learning identified and incentivized the release of 735 hours of block time and made automated offers for nearly half of that time, resulting in 336 hours of OR utilization in one month that otherwise would have gone unused. "Why that is so incredible is we are running maybe three fewer ORs than we have historically, yet our surgical volumes have not gone down," Ms. May said. "We are taking unused time and marketing it to high-margin, elective cases."
Qventus has also enabled Saint Luke’s teams to better adapt and be more efficient. “Previously, we used our EHR to schedule with, but it's a static tool that didn’t factor in the constant changes that are happening in our surgeon scheduling behavior,” said Ms. May. “Now, if a surgeon suddenly starts scheduling short cases on a Monday outside of his block, Qventus picks that up immediately and he starts getting Monday's OR time suggested to him that is open. We no longer have to manually absorb all of this information and try to be efficient.”
UAMS experienced similar results, releasing 545 hours with 51 percent of those going out in automated offers, which resulted in 278 hours being utilized in the last month alone. Ms. McCartney explained that in the past when ORs were blocked but remained unused, staff were sent home because the cases were not available. "Next month, we are starting open scheduling for blocks that are not assigned to anybody as our volume has now increased so much that we need to open up more operating rooms."
By utilizing AI, ML and automation, perioperative services can release more block times earlier and can use information to personalize offers to the surgeons they would most like to fill those OR spaces.
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