Delivering Data to Prevent Early-Term Deliveries

April 10, 2013
Three years ago, when North Memorial Health Care expanded, leaders at the Robbinsdale, Minn.-based health system knew they had to invest in analytics to bring disparate systems together for real-time usage. The organized used the new analytics platform to reduce the number of early-term deliveries and earn a nice financial reward in the process.

Three years ago, when North Memorial Health Care expanded to a second hospital and created a more enterprise-based environment, leaders at the Robbinsdale, Minn.-based health system, knew that analytics would have to factor into the organization’s growth. In terms of how they had previously looked at data, Jon Nielsen, M.D., medical director of women & children’s services at the health system, says the organization was a bit “disjointed” and “sort of old school with our peer review and quality process.”

According to Nielsen, what North Memorial needed was a “tune up.” The organization turned to Health Catalyst, an analytics platform software company based out of Salt Lake City. The software North Memorial invested in from Health Catalyst took data from disparate systems and sources and stored it in an electronic data warehouse. From the warehouse, the data was sent to physicians for real-time usage.

Using analytics for enterprise population health management has become a trend in the industry, with well known healthcare systems such as the University of Pittsburgh Medical Center (UPMC) health system investing millions in this area. The idea is these kinds of analytics capabilities will be able to help the provider move the needle on areas such as diabetes management and cancer treatment. The leadership at North Memorial looked at another “sexy topic” in this regard: early-term deliveries (defined as pre-39 week surgeries).

This is a part of a nationwide effort, lead by organizations such as the American Congress of Obstetricians and Gynecologists, in trying to reduce early-term deliveries and elective C-sections.

“We looked at our numbers [of early-term deliveries] and compared them locally and nationally, and we thought ‘we can move those numbers,’” Nielsen says. “In my mind, knowing the next step would be to then reduce C-sections, and focus on that and then reduce overall C-sections. It’s a process we took incrementally and knew where we were going to end up.”

Reducing Early-Term Deliveries

Over the course of the six-month pilot, North Memorial reduced its rate of elective early-term deliveries by nearly 75 percent.  The data from the analytics platform was able to help physicians and nurses better recognize when the dangerous surgery was appropriate and when they could go another route. As a result of lowering early-term deliveries, one of North Memorial’s payers awarded the organization $200,000.

Nielsen says one of the important ingredients to creating a better analytics platform was an optimized electronic medical record (EMR). North Memorial was able to do this through its EMR vendor, Epic Systems Corp. (Verona, Wis.). Along with this EMR optimization, he says North Memorial leaders were able to engage physicians by creating a clinical review team that analyzed the information that was presented to them, done by the core process team.

“On the quality side, we spent a lot of time identifying which indications for elective induction or repeat C-sections were appropriate. We went through 6-8 iterations of that. When we finally got that list, we could get a hard stop based on that. We could engage the nurses to be the messenger of that but not the enforcer. We created a situation where the doctors understood, based on science you shouldn’t do this, and if they did, the system would catch them,” Nielsen says.

This clinical data could also be presented to the patient, to show them that an early-term delivery might not have been the smartest idea, he notes. Furthermore, it wasn’t just clinical data that was being stored in the electronic data warehouse. It was data from “all different angles,” he says. The warehouse allowed for flexibility and ease-of-use, unlike the previous method of doing this sort of thing, which was a manual input into an Excel spreadsheet.

Looking Ahead

The biggest challenges, Nielsen says, were around changing the physician culture. North Memorial had to make physicians understand that the decision was data-driven and educate them to work collaborative with the nurses. It wasn’t until North Memorial got everyone in the room to understand why the data was telling them certain things, that there was a change in the mentality. Part of this process, he says, has been empowering the nurses to make a decision and have a discussion with the physician.

After early-term deliveries, Nielsen says the organization has looked to reduce the number of C-section procedure rates. Already, this work has begun and North Memorial has already achieved some of its goals. The next step is to reduce the overall C-section rate. It’s not just data analytics in women’s and children’s services, where Nielsen works, but across the enterprise as well. He says they have looked at using analytics for diabetes and cardiovascular clinical management, acute care medicine, and lab protocols.

For those who wish to undertake something similar, Nielsen recommends looking outside the organization. “Most people cannot start from internal and have all the pieces together. You got to look towards your consultants, who can get your business started, train you, and eventually sunset themselves. That’s what consultants usually do,” he says. In addition, it’s about looking ahead.

“If you think about ROI [return on investment] in your first year, you’re not looking at the big picture.”

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