Bringing Factory Thinking to Healthcare

Optimizing block scheduling for hospital operating rooms is a potential cost savings for health systems. Having the right tools and the right data is imperative.

While it’s possible to bemoan the industrialization of healthcare, when large amounts of resources— represented by operating rooms, hospital beds, and staff—it is essential that healthcare systems look for inefficiencies and squeeze them out.

Toward that end, Mercy Medical Center, an 875-bed operating unit of Catholic Health Initiatives in Des Moines, Iowa, recently turned to cloud-based analytics software from Hospital IQ (formerly PatientRoute) to improve patient flow, reducing backups in the emergency room, and to better meet surgeon demand for operating rooms.

Mercy’s path to Hospital IQ began several years ago, when Kathy Goetz, vice president of perioperative and specialty services, attended a meeting convened by the Institute of Healthcare Optimization about how to do more to optimize scheduling people, rooms, and equipment.

“I was introduced to some statistical theories about how to help manage the flow of patients with a concept called the queuing theory,“ Goetz says. “That’s the concept of how do you help get things through a system. Queuing theory basically talks about when you have people standing in lines, how do you get them through? If you think about having four tellers at a bank, and you’ve got five people in one line and seven in another line and three in another line and eight in another line, how do you decide at what point you’re going to open up a fifth line? Or are you better to shut down one of the lines and consolidate your resources and have everybody go through three lines?“

Queuing theory is a fairly simple concept, but not so simple to implement without algorithmic help. Still, many industries, such as banking and grocery retailing, have applied the theory to good effect, as witnessed every time a supermarket opens a new checkout line when demand for clerks soars.

“I became very intrigued by the idea and came back and tried to implement some of the concepts, but found that what we lacked was the statistical software to help us be able to analyze our current flow data, and also to enable us to do some simulation modeling,“ Goetz says.

Through the Institute of Healthcare Optimization, Goetz found Hospital IQ. “We spent some time looking at what we thought the return on investment would be for our organization if we were able to utilize those tools,“ she says. In fall 2015, Mercy began its formal partnership with Hospital IQ, which began to send staff to Des Moines monthly to identify the data needed from Mercy to input into its analytics software.

‘A Big Surgical Factory’

One of the most challenging resources to optimize is block scheduling, which is the way surgeons use specific blocks of time, a resource most electronic health records do an inadequate job of optimizing. Block scheduling is made complex by the fact that different surgeries and surgeons require different lengths of time.

Since operating rooms can cost $60 per minute to run, making sure those ORs are not prepped-but-idle is a real area of potential cost savings for health systems.

“You want to get the most out of that time and understand who’s using it well and who’s not using it well,“ says Rich Krueger, CEO of Hospital IQ. Kruger comes from outside of healthcare, from virtualization software vendor VMware, and has a background rich in the theories of W. Edwards Deming, who championed quality control and management theory in the post-World War II era.

“The way you run the operating room, it’s a big surgical factory,“ Krueger says. “Most of your procedures are elective. Some percent are urgent or emergent, trauma cases or work-ins or whatever, but a lot are scheduled, and surgeons need to know when they can schedule patients.“

Until now, institutions such as Mercy have tried to fill the analytics gap with those time-honored healthcare analytics tools, the spreadsheet and the report writer. And for smaller hospitals, such solutions will suffice. But as Krueger puts it, “the bigger the system, the more complex the factory“ and thus the need for the kind of visualization that Hospital IQ provides.

At Mercy, decreasing overtime and meeting surgeon demand for increased caseloads is essential, Goetz says. It has engaged Hospital IQ “to assist us in looking at our overall hospital throughput, from patients that present either through the emergency department, through admitting, through procedural areas for admission after the procedure—whether it’s in surgery or cardiac catheterization labs—or [for] different imaging-type studies to help us as we have encountered some issues with boarding of some patients in our ED because our inpatient beds have been occupied.”

Granular and Visual
Because of the way the software is built, it is much easier for Goetz and her team to drill down to the case level, sitting next to a physician, to show them resource utilization and patient flow which need attention. “That sort of granularity is not something that we’ve had available to us through our electronic medical record or other programs,“ she says.

One of Hospital IQ’s more intriguing features even allows users to replay the data by watching actual resource utilization over time and look for ways to smooth perioperative and inpatient elective procedures, whether through staffing up, staffing down, moving staff around, or even moving patients around.

“You want to precisely manage inpatient resources and beds and staff to what actual demand is,“ Krueger says. Setting up Hospital IQ requires getting the needed data out of a multitude of existing data systems at health systems—bed management systems, alarm systems, scheduling systems, and EHRs, among others.

Finally, as with much of the recent wave of analytics technology, Hospital IQ is able to take the data it ingests and predict patient and surgery demand by such parameters as day of the week or month, and the impact such predictions will have on wait times for ORs or regular beds or ICU beds. Then there are the long-term trends to keep tabs on, such as decreasing length of stay, which also factor into the software’s predictions.

At this point I wondered if enterprise resource planning (ERP) software, which larger healthcare systems already use, provides some of this predictive capability.

“We’ve met with hundreds of customers, or probably a hundred at this point. You’re the first person that has ever asked me if any of the ERP systems does this,“ Krueger tells me.

“In fact, one of the ERP vendors that we discussed is actually interested in partnering with us because they’re looking at all the operational data. We’re reconciling things like orders and movements and timestamps—a lot of operational details that are not in ERP or supply chain systems.“

Back at Mercy, use of the technology is still too fresh to have measureable outcomes, but such data is imminent, Goetz says. Part of this is because the underlying data Hospital IQ is drawing upon at Mercy is itself somewhat of a moving target.

“We recently had some changes in our financial software that we use, and so trying to go back and say ‘OK, if we’re going to look at the data for a six-month period, we have it for four months in the old system and now we have two months of data in the new system.’ You don’t want to be using data that’s not really representative of where you are today,“ Goetz says.

“Now we’re at the point where we’ve identified where we think the majority of the information is going to come out of, and we’ve gotten enough data sent and validated that the data will come across… Now I think we’ll be able to move forward rather quickly and get some really quick wins.“