How Data Analytics Can Help Manage Intensive Care Unit Capacity
Data analytics tools can help hospitals manage patient capacity and flow in intensive care units, particularly during COVID-19 surges.
Source: Thinkstock
By Jessica Kent
- Data analytics tools have proven to be valuable assets in several areas of healthcare. From disease detection to workflow optimization, advanced analytics solutions have the potential to increase care efficiency and enhance day-to-day operations.
At University of Colorado Hospital, leaders recognized the need for advanced tools to help manage patient flow in the intensive care unit (ICU).
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“Our organization has grown very rapidly over the last several years. We’ve developed several homegrown tools that help us utilize data, which has been great. But the downside is that it has resulted in a lot of manual labor on our end,” Jamie Nordhagen, Director of Capacity Management at University of Colorado Hospital, said during a recent episode of Healthcare Strategies.
“Our frontline clinicians have to spend time gathering data to operate daily, and this ultimately resulted in a lot of chaos. We spent a lot of time in daily operations to make sure that patients flow through our hospital and we have enough space to accommodate our patients. We really needed a solution to help reduce this burden.”
Nordhagen and her team deployed an advanced analytics tool to help detect when the hospital’s ICU is nearing maximum capacity, enabling them to move patients to areas where resources aren’t as strained.
“The tool has been really instrumental in automating patient flow through our ICUs. COVID-19 surges really complicated our patient flow, and the tool has allowed us to manage the influx of patients during these times,” Nordhagen said.
“Our bed management system used to require our nurses to manually enter when patients were ready to move, after physicians wrote downgrade orders for transfer to lower levels of care. The solution has allowed us to leverage a pull versus a push strategy for our lower acuity patients in the ICUs. And it's also offloaded some of that administrative burden for our bedside nurses.”
In order to successfully deploy a data analytics solution, Nordhagen noted that clinicians must play a role in its design and implementation.
“Pull in your operational and clinical leaders as soon as possible, because they're the people that really understand reality and logistics. The more that you can pull them into the building of the tool and how it works, the more you can increase their trust in the tool and how they utilize it,” she said.
With this advanced analytics tool, Nordhagen and her team have been able to improve provider workflows – a critical advantage during the pandemic.
“We can now look at how we're utilizing our space across the region and where our available beds are. We can see where our COVID-available beds are and what our census is. And we can start to look at our COVID-19 protocols and where we can place patients as they come in through our access centers,” Nordhagen concluded.
“The analytics tool has been pretty instrumental in us running our unit and keeping access available for not only COVID-19 patients, but other patients across our entire system.”
