Four ways to get your data analytics team up to speed
The costs and resources needed to operate and maintain a data analytics team at a healthcare organization will continue to rise. But experts say the benefits should have a positive effect on all areas of business.
“The data analysis team can work with the rest of the organization to find the right questions to ask. This will produce the outcomes and deliverables that are valuable to the whole organization,” says Gerard M. Nussbaum, director of technology services at Kurt Salmon in New York City. “Having an analytic staff to draw valuable data that helps the business learn, decide, and act is invaluable to moving the business forward.”
And, for many organizations, having data scientists on-site is no longer a choice; it’s the standard, says Nussbaum. “People on your team understand your business, the type of data you need, and are quicker access,” he says. “It’s tough to find good people in this field and keep them—people who understand not just generic health plan information, but your business.”
Find the right structure
While it’s a good idea to have some in-house staff dedicated to analytics, some organizations find that mixing in some outsourcing can be effective, says Michael Vennera, chief information officer and senior vice president of Independence Blue Cross.
For example, one team might use a mix of outsourced analytics from a vendor, and also have one or two in-house scientists and other existing staff who are trained in analytic-thinking, he says.
“One of our value propositions is the data we have about our members,” Vennera says. “That’s one of the big places that we can make a difference in the marketplace. So we have to be very careful in making [outsourced data] decisions. You have to be able to balance what you need with what you can afford.”
Still, he says, a lot of analysis is available in the market, so it doesn’t always make sense to “reinvent the wheel.”
Find the right staff
Analytics teams can have several makeups depending on the needs of the organization. For example, Pamela Peele, PhD, chief analytics officer at UPMC Health Plan, Inc., says their analytics department is its own department (separate from IT) and has its own budget. As the department head, Peele reports directly to UPMC’s CEO.
She is a champion of this set up, saying that having a budget and staff solely for analytics allows the department to set its own strategy.
“I don’t think the analytics team belongs under the CIO. The CIO is looking at technology, security and privacy, not looking at secondary analytics and knowledge discovery,” Peele says. “Being separate makes analytics a distinct and integral part of the organization.”
The UPMC analytics department is made up of a range of specialists, including scientists, mathematicians, and epidemiologists. Forty team members work specifically in the analytics department, and other analysts work in other departments, such as pharmacy, marketing, and maternity. In total, Peele says UPMC staffs approximately 100 data analysts.
“People who are hired to do analytics aren’t just IT. They are true analysts, scientists, physicists, and statisticians. We even have an epidemiologist on our team. It’s not usually a team of people that would be in an IT group,” Peele says.
Nussbaum says a more traditional structure for an analytics team it is to position it within the IT department, while working with other departments.
“The data analysts must work with IT and business groups at carefully defining the right questions and answers that will help the business,” he says.
Creating goals and measuring success of the data analytics team is critical, says Peele.
“Short term and long term, front and center of our goals is to influence the organization,” she says. “The value of analytics at any organization is how much it influences the organization. If you are investing money and never change decision making, you’re wasting time and money.”