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Mercy Health System Saves Millions on Nurse FTE Leakage with Data Analytics

One of the largest expenses health systems incur is nursing labor. At Mercy Health System, headquartered in St. Louis, Missouri, that expense hits $880 million each year. Mercy is the fifth-largest Catholic health system in the U.S.

Many things factor into that cost, but executives needed to find a way to get control of it – and one of the main issues was full-time equivalent (FTE) leakage among their nurses. FTE leakage refers to the number of hours an employee was expected to work versus the actual number of hours worked.

Mercy’s FTE leakage reached 80,000 hours per year across 630 units in 44 hospitals, which caused system executives to rely on agency nurses to fill in that time.

To fight the FTE leakage, Mercy Health developed a tool that takes data from the hospital’s software as a service (SaaS) scheduling application and looks at it through a predictive analytics lens. By doing this, schedulers can find leakage issues and fill in the missed hours with their own employees.

Since implementing the system, Mercy Health has seen a savings of $4.3 million. They began the process of analyzing FTE leakage in 2015, and in September 2016, they implemented the current system.

Getting the Data Right

At the 2018 HIMSS Conference, Mercy Health Vice President of System Operations Mike Gillen and Chief Nursing Officer Stacy Blankenship of Mercy Hospital Jefferson presented their strategies and explained how using advanced analytics helped them reduce FTE leakage.

“We had to get the data right,” Gillen said. “You have to understand the metrics. Someone would say I was on PTO, well that isn’t leakage. We had to take some of the noise out too. There’s a 90-day orientation period, but our systems would say we had another nurse on. Well not really, and that shows as leakage. It’s not, that nurse is just in training. Nurses in multiple units is another example, so we had to have the systems understand this.

“We had to use technology to make it so nurse leaders could see the leakage. Once they could see it, they could fix it. Once we started to build a dashboard, that’s where we really started to see the magic happening. It brings it all together, it’s convenient, it’s actionable and it drives performance,” Gillen said.

Outlining the dashboards to see leakage hours at the community level can identify how hospitals can help each other. It can be broken down by cost centers so at the director level, executives can drill into where the money is going.

Sharing Clean Data for Collaboration

“One of the most important things from my perspective was building collaboration among nurse leaders,” Blankenship said. “It was vital for our labor strategy, because nurse leaders not only heard responses from the team but would meet in person to collaborate on solutions. Sharing clean data with them so that they can make their strategies, so they aren’t glued to the phone all the time trying to get nurses to come to work as they try to find ways to fill the gaps.”

They developed a definition of standard work at multiple levels of the organization and reviewed it at the manager level. The directors are approving the schedule the managers make and the team is reviewing the dashboard every day as part of their standardized work. Then they can identify where leakage is occurring and addressing it.

A scheduler can identify when a staff member is leaking time and can redeploy them into the schedule before a pay period ends, covering the hours that were lost and ensuring that the staff is meeting full-time requirements.

Increasing Nurse Engagement and Analyzing Other Metrics

Nurse engagement has been important. Maintaining a proper, balanced schedule reduces turnover and increases buy in.

“In May 2016, 1-in-4 nurses was leaving. That doesn’t drive a positive culture. Through this project, we were able to reduce RN turnover to 12% over 12 months, and we have nurses more focused on driving patient engagement and improving patient outcomes,” Blankenship said.

“I think we could have gotten to our results faster if we spent more time understanding the data,” Gillen said. “You have to check it every day, and that is part of that standardized work for nurse managers. And of course, you can’t underestimate training. Data isn’t as self-explanatory as we like to think. The training answers the questions of what to do with it, how can it help?”

They plan to also track nurse satisfaction in the future to see if this affects those rates as well, and believe that this could open the door to other opportunities to save time and money.

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