Hospitals have to solve a thousand logistical challenges every day, but perhaps none are more difficult than operating room schedules.
Surgeries can be difficult to predict — in fact, less than half of surgeries in the U.S. start and end on time. That can create chaos for patients and doctors, and costs hospitals $5.2 billion every year, according to University of Washington spinout Perimatics.
The startup, which develops a variety of technologies for hospitals, is taking aim at the operating room problem with a new AI technology that uses data on patients and surgeons to more accurately predict how long each surgery will take.
The startup recently deployed the technology at a large academic medical institution in Seattle. So far, it has cut the number of surgeries that run over their scheduled time by 20 percent, a result that could save a hospital $1 million a year in staff overtime alone.
The startup is still studying how its technology affects underage, or the number of surgeries that end before the predicted time, and other elements including patient and employee satisfaction.
Perimatics’ algorithm begins by looking at a patient’s data and seeking out information that will affect how long the surgery takes, like the patient’s prior surgeries and their age.
Kalyani Velagapudi, Perimatics co-founder and CEO, told GeekWire that the surgeons themselves also have a big impact on how long a surgery takes. Each surgeon approaches an operation differently and will bring in various factors that affect the length of the operation.
“That was a surprise,” said Bala Nair, Perimatics’ chief solutions architect and co-founder. “We had to build machine learning models customized for each surgeon.”
The algorithm also takes into account the staff that will work on the procedure, like anesthesiologists. It can also suggest last-minute scheduling adjustments when operating rooms are needed for emergency procedures.
The end goal is to help hospitals cut down the $5.2 billion a year that results from overage and underage in surgeries. In addition to staff overtime costs, operation rooms cost an estimated $62 a minute to run, so any variation from the set schedule can quickly become extortionate.
That’s not to mention factors like patient and employee dissatisfaction, which is also a common side effect of scheduling challenges.
Although this is the first time the technology has been deployed in a hospital system, Nair said it is easily scalable. Now that Perimatics has worked out which factors impact surgery length, the basic framework can be applied to almost any hospital, he said.
Velagapudi said the startup is continuing work on its other AI technologies, including its Smart Anaesthesia Manager. That program, invented by Bala, analyzes a patient’s health metrics in real-time during surgery and helps doctors make decisions that have a big impact on a patient’s health when they are recovering.
She also said the company is working on new solutions for post-surgery problems and surgical supplies.
“It is quite different from the data science that is being done on the market today because it is real time,” Velagapudi said of the startup’s work.
Perimatics spun out from the University of Washington last year and currently employs 7 at its headquarters in Bellevue, Wash. It is also a partner of Microsoft for Startups, the tech giant’s startup assistance program.