How Do I: Synthesize Nursing Data Efficiently and Effectively?

To ensure big data is used to influence outcomes that are meaningful to the nursing profession, nurse executives need to act as data visionaries and architects. But how?

Have you ever found yourself poring over stacks of data, feeling more like a statistician than a nurse? If you have, welcome to the world of big data.

"You have all of these different data sources coming at you on a weekly, monthly, quarterly basis. The CFO has a stack of data for you, your productivity-management engineer people have a stack of data for you, HR has a stack of data for you, and then your quality director, your clinical folks, have a stack of data for you," Jane Englebright, former chief nursing executive and senior vice president at Nashville, Tennessee-based HCA, previously told HealthLeaders.

"And your job is to sort through all that data and synthesize it in some way and come up with brilliant conclusions about how to run the organization," she said.

But how can it be done efficiently and effectively?

When a CNE is analyzing and synthesizing data, it's typically done manually and is a very time- and labor- intensive process, in part, because technology systems have traditionally been built in silos. "Often they don't even call the units the same thing. They don't name them the same thing. They don't necessarily define them the same way," Englebright said.

For example, the definition of a day may vary from system to system and the way a month is calculated in the finance systems may differ from how it is calculated in the payroll system.  

Trying to "figure out how to keep up with your agency hours and what the cost of your agency is in the finance system versus the scheduling system," Englebright says, is "just a nightmare, trying to make all of these different things sync."

The lack of data standardization can also make it challenging for a CNE to assess how the organization or a particular unit is performing and to make well-informed decisions about what to change. Having good data is key to making effective changes.

"For those of us who grew-up studying the biological sciences, we understand that we have taken a very linear, Newtonian-approach to data over something that's really much more like a biological system," she explains. "When you perturb one part of our system… it has ripple effects throughout the entire organization."

Failure to recognize how this data interacts throughout the system has been a limitation in the types of data analytics that have been put forth.

"The frustration that we often have as nurse leaders in looking at this data, is [that] some of the variables we care about the most, aren't even in the data," Englebright says. "We don't have something that measures nursing competence, for example. We don't have something that measures how committed the nurses are. We don't have something that measures if the patient really [is] going to do the stuff we just invested all this time in teaching them to do."

Because of this, CNEs end up having to advocate for the things they care about in a person-on-person debate, rather than being able to make a persuasive business case based on data, she says.

For all its current stumbling blocks, big data holds the potential to change healthcare delivery for the better. But for that to happen, nurse executives need to act as data visionaries and architects.

To support CNEs in doing this a workgroup that grew out of the University of Minnesota's annual Nursing Knowledge: Big Data Science Conference developed the CNE Big Data Checklist.  

It outlines three main areas where nurse executives should become leaders in driving the use of big data:

1. To create a culture that thrives on data
2. To develop big data competencies for the organization
3. To create an operation infrastructure to support big data use

This article is part of HealthLeaders’ How Do I? series. Read the entire article here.