How Hospitals can become Data-Driven Businesses and Optimize Operation Room Planning

Surgeries typically contribute approximately 60% of a hospital’s total revenue. However, over the last two years, while the healthcare industry was at the front line of combatting the Covid-19 pandemic, countless elective surgeries were postponed or canceled. Now, many hospitals face a revenue deficit and, notably for public systems, , dramatically increased procedure wait times, exacerbated by a global wave of staff shortages.

At the same time, hospital Operation Rooms (ORs) also represent major cost centers, especially when they aren’t operating at peak efficiency. And any inefficiency slows down their ability to address a backlog of surgeries to reduce waitlists.

OR scheduling is a black art that requires delicately balancing countless different variables. For a start, each hospital has a finite number of ORs and multiple other specialties that need OR time allocated – from urology to neuroscience and orthopedics. Each specialty has numerous surgeons, who each have individual preferences regarding how they like their OR set up and whose surgeries require different lengths of time. Each of their surgeries also requires multiple other specialists – such as anesthesiologists, technicians to operate various pieces of equipment, scrub and circulating nurses. In some cases, other disciplines, such as phlebotomists or cardiologists must be available because of a patient’s various comorbidities. The downstream considerations also need to be considered, such as the availability of post-anesthesia or ICU beds. And if that’s not enough – things change - constantly. Equipment breaks, staff call in sick and patients cancel.

To manage these variables – operating room time is arranged in blocks, but this only accounts for a few variables, and decision making is not data-driven. It’s not uncommon to find that specific slots are allocated to surgeons just because it’s always been done that way. The same time might be allocated for the same procedure, even when the data shows that different surgeons require longer or shorter timeframes. There’s also the challenge of balancing the equipment needed for operations, which may limit which surgeries are handled simultaneously.

There’s no shortage of data relating to this multitude of factors – however, it’s almost impossible for hospitals to use it in decision making. Subsequent delays or inefficiencies represent multiple resources, from staff to equipment and facilities that are essentially on the clock but not generating revenue.

That’s because the sheer number of moving pieces makes it impossible to keep track manually, and as the variables increase, so does the scale of the computing challenge – quickly putting OR optimization beyond the capabilities of today’s classic computer processors. As a result, hospitals do not effectively leverage the data they collect and expensive OR resources are not optimized.

But there is a new Fujitsu system designed to support OR scheduling to help increase revenue or reduce patient time to surgery by fitting in additional surgeries or by closing unused operating rooms to reduce costs.