Like every health system, Allina Health, based in Minneapolis, Minnesota, relies on surgical procedures as a core financial driver.
PROBLEM
In 2018, as part of an overall health system initiative to improve patient flow and increase capacity, Allina sought to optimize its surgical services by eliminating more waste and inefficiencies in every surgical procedure – from the time the surgery is indicated in the clinic to the day of surgery. surgery and discharge from the PACU.
“Our hypothesis was that there were cases of surgery where we lost due to the inconsistent and unpredictable procedure of a single day of surgery, so we wanted to use standard work in the ORs of ourselves to ensure our patients and surgeons experience as predictable a day of surgery as possible,” explains Bill Evans, vice president of surgical and orthopedic services at Allina Health.
He continued: “An important part of reimagining surgical services is creating a system-wide surgical scheduling policy to fill up time OR more efficiently. “However, even after standardizing our scheduling processes to maximize OR usage, we believe there is still significant room for improvement.”
For example, surgeons looking for locations outside of their assigned block time, as well as newer surgeons looking to establish enough volume to justify assigning a block, has been hampered by manual scheduling processes that have not changed significantly in 30 years. Those processes also frustrate both ORs and those who schedule visits, leading to low levels of job satisfaction.
Evans notes: “After improving every part of the process chain and addressing the use of ORs through policy, we remain confident we haven’t addressed the accessibility issues that surgeons have Our technicians told us they were having trouble.”
He continued: “In particular, our robotic surgeons have told us that they are inaccessible despite the low utilization rate. “It was clear that we needed a new approach to surgical scheduling, and we believed we needed a purpose-built solution to address the unique challenges of OR scheduling – and be designed around surgeons.”
He added, Allina Health simply cannot afford to wait for its supplier of EHR or other IT systems to finally roll out something like this.
PROPOSE
Before making any recommendations, Allina Health worked with healthcare IT provider Qventus to thoroughly study its situation, systems, and current and future needs.
“They met with all stakeholders to make sure they understood the difficulties and challenges,” recalls Evans. “Ultimately, we chose Qventus to allow us to automate our operating room schedules and maximize our surgical programming with the help of machine learning artificial intelligence.
He continued: “The perioperative solution that Qventus proposes will automate and unify scheduling OR, while providing greater efficiency and reducing the burden on overworked staff.” “The Qventus perioperative solution automates every step of the scheduling process and eliminates manual processes that cause bottlenecks and schedule mismatches.”
The system’s AI-powered software combines pattern recognition and prediction with principles of behavioral science to solve Allina’s serious scheduling problems.
There are a few key differences between Qventus’ technology and other vendors’ technology that make Evans and his team stand out.
“Predictions alone do not drive value, they must drive action,” he said. “That’s where Qventus applies their behavioral science expertise. When they push block holders to release early, they show them ‘What’s in it for me’.
He continued: “Surgeons don’t lose much of their time when it comes to early time release, but their advantage is improving their block utilization – and the priority is to be informed about future available time. future”. “Moreover, the system not only predicts that a block will be underutilized; it actually predicts specific idle times for easy action by block holders.”
Allina Health is also looking to increase the number of cases.
“Some solutions use machine learning to ‘reserve’ their ORs to fit more cases, which introduces significant risk and frustration,” argues Evans. “Moreover, other tools simply bombard practice activities with open time alerts when time runs out.
“We wanted to build a case mix that would help achieve our strategic goals: optimize location of care, develop strategic service lines, build relationships with key practices, etc,” he continued. “Machine learning helps us attract cases that match our priorities.”
When practices – including independents – seek time, they personalize how open time outcomes rank based on practice patterns and health system priorities, in the same way that Netflix learns viewing patterns and makes recommendations.
Allina Health’s system doesn’t just wait for cases to arrive. When given time, machine learning will match available times with suitable surgeons and proactively provide them with time, much like how Amazon sends product recommendations based on pattern purchases.
“In a nutshell, the ‘push/pull’ capabilities I’ve described, on an automated machine learning platform, are exactly what we were looking for to help solve our access issues, ‘ said Evans.
MEET CHALLENGES ONLY
Allina Health has gradually rolled out the system over several months at its flagship hospital, Abbott Northwestern, starting with robotic surgeons who have been the most vocal about accessibility issues.
The second phase includes all block-time holders and the third represents all surgeons with hospital privileges but no block-time holders.
“We chose to use the system voluntarily rather than mandated and deliberately positioned it as a tool to assist surgeons, although its use would also allow we optimize and develop our surgical services”. “Currently, more than two out of three electives are scheduled through Qventus.
“Our phased approach has been very successful from the start,” he continued. “In the early days, we exceeded our performance goals, and the tool was so intuitive, we started seeing cases added from surgeons who didn’t plan for Phase I but am seeing how it can help their practice.”
After staff worked with all Phase II block holders, they were delighted with the results in terms of surgeon uptake, but also freed up unnecessary block time earlier to other surgeons can use.
RESULT
Allina Health’s results since launching Qventus in mid-2022 are impressive:
“On average, we added 3.5 cases per OR per month,” Evans reported. “Additional cases mean greater revenue, shorter patient waiting lists, and busier and more satisfied surgeons.
He continued: “We have increased the number of cases per surgical robot by 36% per month. “In the past, it was difficult to efficiently schedule robotic ORs resulting in robot-equipped ORs not always being available when needed, and non-robot procedures sometimes being performed in rooms equipped with robotics. by a robot.”
Over 100 hours of OR block time were released early each month. This is very beneficial because the earlier the release time, the more likely it is that it can be filled by another surgeon. The Perioperative Solution automatically prompts the surgeon to release periods they are not likely to use, which creates greater efficiency throughout the system.
“Two out of three electives are automatically scheduled through Perioperative Solution,” notes Evans. “This level of automation eases the burden on our schedulers and surgeons’ schedulers. It frees them up to perform more important tasks.
“Often we hear from our clinics that we’ve made scheduling so easy that we’re the default solution they always use first,” he added.
The perioperative solution has exceeded Allina Health’s expectations from a quantitative outcome perspective right from the start.
“But just as importantly, it provided our scheduling teams with an innovative tool that made their job easier,” says Evans. “It frees up time for them to focus on more complex scheduling cases and provides a higher level of communication for our teams, rather than asking for the usual low-value tasks, like such as handling back-and-forth phone calls and faxes.
He added: “I believe we will see additional unplanned savings as a result of reduced turnover in our planning staff.
TIPS FOR OTHER PEOPLE
“Automation powered by artificial intelligence and machine learning is the future of healthcare,” says Evans. “It’s the obvious and necessary answer to staffing shortages, rising labor costs and shrinking surgical revenue.
“Many health systems are waiting for their EHR or other IT systems to implement these types of solutions,” he concludes. “However, waiting comes with a significant opportunity cost. These automation solutions have a quick ROI and are purpose-built to solve these unique problems; EHR and other systems. not.”
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Email the writer: [email protected]
Healthcare IT News is a publication of HIMSS Media.
