Article

3 Reasons Your Healthcare Organization Needs an Analyst Group

Contributing Lab Leaders: Joe Dudas, MBA; Brian Jackson, MD, MS; Peter Gershkovich, MD; Ed Hammond, PhD; and Terry Carroll

Operational

Article highlights:

Healthcare systems can benefit from establishing an analyst group to help translate their data into action.
Analysts can help optimize complex care, find fresh solutions, and break down silos.
The analyst group must be positioned correctly in the organization to be accepted by the potential users of the data.

The healthcare world is swimming in data, from insurance claims to electronic health records to patient monitoring devices to the bar codes on every IV bag and vial. Analytics, the software containing the algorithms that try to make sense of data and improve patient care, are becoming a standard part of the healthcare IT toolkit. But do healthcare systems still need actual human analysts in addition to this technology?

It depends, says long-time healthcare CIO Terry Carroll, who works with the SPRING Network, an organization devoted to organizational change. “Not every organization can have this kind of capability," he says. Smaller or rural hospitals, for example, need to devote their limited resources to day-to-day delivery of care. But healthcare systems with more money and more diverse missions—and especially those that do research— may need human beings to make sense of data and explore ways to apply key findings.

Discover, Translate, Apply

Joe Dudas, division chair of Enterprise Analytics at the Mayo Clinic, thinks of analytics deployment in three phases: discover, translate, and apply. Analysts work in all three phases, but particularly in the “translate" phase, taking the insights produced by analyzing the data and working with users to move them into action.

Your organization may use an analyst, or a group of analysts, to help with:

Optimizing complex care. At the Mayo Clinic, physicians have established a number of registries to collect data on various aspects of patient care, which analysts can use to produce the best treatment options on complex cases and spread the experience of the clinic's world- class experts as widely as possible. “We can build very specific tools that give physicians insights that maybe the most experienced physician might have, but maybe all the staff does not have," says Dudas. “Our goal is not necessarily to make the best better, although that happens, but to bring the rest up to the same level as the best."
Finding new approaches. The information presented by an analyst group can allow departmental leadership to identify problem areas more accurately and reframe their solutions, Carroll says. “If you're struggling with making progress, you have to change the question."
Breaking down silos. In organizations where clinical departments are used to working with data in isolation, an analyst group can help integrate the information to obtain a bigger picture understanding. “Academic medical centers are the worst, where every clinical department is a really hardened silo," says Brian Jackson, associate professor of pathology, University of Utah, and chief medical informatics officer, ARUP Laboratories. “The data silos are a symptom and a consequence of the organizational silo. I don't see a lot of healthcare organizations with strong clinical metrics across the whole organization that everyone takes seriously." An analytics function that transcends individual departments can help develop those cross-organization metrics.

On Extending Capabilities

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Terry Carroll

Chief Digital Officer

Spring Network

On Sharing Insights Accumulated through Experience

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Joe Dudas, MBA

Vice Chair

Mayo Clinic

Get the Lab to the Table

It's vital for lab managers to find a way to participate in enterprise-wide analytics projects because the data they can contribute may not be readily understood by analysts who don't have specific expertise in lab matters, explains Peter Gershkovich, director of pathology informatics at Yale University Medical School. "The role of labs should increase," he says. "Analysts don't understand the complexity of the lab data model, and that prevents them from adequately addressing data requests, either for research or for quality improvement."

Ask the Right Questions

Organizations trying to establish an analyst function should think carefully about how to position it in the community, notes Ed Hammond, director of the Center for Health Informatics at Duke University. The best analytics in the world won't change anything unless they're connected to the people who need the insight.

In a study of one department at Duke, clinicians simply weren't using the information provided by the analyst group—except for one researcher who needed material to make slides for a talk. “When you're doing analytics, who are you doing it for?" Hammond asks. “Is it only the research community or is it the clinical community, as well? How do you make the analyst part of the team and get the information to the right people? How much is the analyst responsible to educate the potential users? It's a lot of questions, but you have to ask them to move the analyst function into a broader, more useful spectrum."

Contributing Lab Leaders

Joe Dudas, MBA

Vice Chair

Mayo Clinic

Brian Jackson, MD, MS

Academic Clinical Pathologist, Medical Informaticist, and Laboratory Business Leader

University of Utah; ARUP Laboratories

Peter Gershkovich, MD

Research Scientist, Director Pathology Informatics

Yale University Medical School

Ed Hammond, PhD

Director

Duke Center for Health Informatics, Duke Translational Medicine Institute at Duke University