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Lakeland Regional Health

Lessons from optimization project paves the way for second phase

When leaders at Lakeland Regional Health (LRH) in Lakeland, Florida, wanted to optimize their provider documentation process, they didn’t stop after receiving help from the Cerner Continuous Improvement Delivery (CID) services. They took the lessons learned and kept optimizing other specialties within the health system.

“When it came time to talk about optimizing other specialties, we basically had a wash, rinse and repeat mentality,” said Malcolm Duggan, RN, clinical informatics analyst. “We already had something we knew that worked.”

In July 2019, Cerner wrapped its portion of an optimization project of physician documentation within Dynamic Documentation™ and MPages® solutions. During that project, Cerner trained an LRH employee who then trained more than 220 providers across five specialties on how to utilize the solutions.

When working with CID, LRH providers saw an average 6% reduction in adjusted time per patient.1

“If you can save them one and a half minutes per chart, and they’re looking at 30 charts every day, that’s getting them home 45 minutes earlier to be with their family or at that baseball game,” said Duggan.

“We were thinking throughout the project, how would we do this with other specialties?” said Darin Peachee, IS manager, applications. “What we put together as a team was a great blueprint, and we knew coming out of it that we would be able to take them and move to the other specialties.”

After Cerner’s help with the first wave of optimization, LRH staff continued the process on their own with a second wave. In the next six months, they finished optimizing 37 other physician specialties. Leaders felt prepared to continue the optimization project on their own.

LRH saw an increase in usage of MPages for chart review. When working with CID for the first phase, Lakeland providers used MPages for 40% of the time spent reviewing charts.2 When Lakeland staff continued the optimization project on their own, they spent 47% of the time in chart review utilizing MPages.3

The health system saw a similar result around Dynamic Documentation, with 92% adoption4 in the first wave with Cerner’s help and 84% adoption5 when LRH rolled out the improvements to remaining providers.

Lakeland leaders credit some of the project’s success in gathering physician feedback along the way, as well as support from Cerner.

“We had pilot physicians well in advance of the go-live. After all the building out, I think that was the one thing that might have made us go even further with the success because they were able to give us almost real-time feedback,” said Duggan.

“Cerner was available at all times,” said Peachee. “I could reach out and they would find an answer. Often, I’d get a response immediately. If not, I’d get the answer by the end of the day. That just made the project so much easier. I still talk about it as being a great project and one that set us up for success.”

1 Comparing baseline of 15:17 documentation per patient from Sept. 1, 2018 – Nov. 30, 2019 to 14:18 to Dec. 11, 2019 – March 10, 2020.

2 Comparing baseline of 588,016 seconds in MPages and 15,245,434 seconds of chart review time from Sept. 1, 2018 – Nov. 30, 2019 to 8,354,672 seconds in MPages and 20,998,231 seconds of chart review time from Dec. 11, 2019 – March 10, 2020.

3 Comparing baseline of 564,583 seconds in MPages and 7,555,607 seconds of chart review time from Sept. 1, 2018 – Nov. 30,2018 to 4,963,217 seconds in MPages and 10,635,426 seconds of chart review time from Dec. 11, 2019 –March 10, 2020.

4 Comparing baseline of zero Dynamic Documentation notes out of 81,280 total notes from Sept. 1, 2018 — Nov. 30, 2018 to 90,958 Dynamic Documentation notes out of 98,660 total notes from Dec. 11, 2019 — March 10, 2020.

5 Comparing baseline of zero Dynamic Documentation notes out of 65,285 total notes from Sept. 1, 2018 — Nov. 30, 2018 to 60,261 Dynamic Documentation notes out of 71,515 total notes from Dec. 11, 2019 — March 10, 2020.

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Client outcomes were achieved in respective settings and are not representative of benefits realized by all clients due to many variables, including solution scope, client capabilities and business and implementation models.