When it came to bundled payments, Signature Medical group didn’t just dip its toes in the water. It got involved in a significant capacity, engaging with providers across the country and with 50,000 patients a year through its bundled payment system.
But that required a better approach to utilizing data analytics, so the team stopped outsourcing and moved its operations in-house.
Now, they’re mining better data, doing it faster, and using that information to improve everything from patient outcomes to their own bottom line.
“We initially outsourced a lot of our technology needs to other companies that were experienced or had been in this space before,” said Jim Gera, Signature’s senior vice president of business development. “Eventually we just kind of hit a wall with each of those companies where there were some good things going on, but we were just limited. We weren’t getting the type of analytics and reporting that we needed to get the physicians engaged in all of the different settings we were in.”
What’s common with many systems, Gera said, is that they’ll use one report, and send one dashboard, to all of its physicians — which can be helpful in certain circumstances. Signature, though, developed five standardized reports that it uses, with numerous filters that can be tailored in a specific manner. That specificity made a difference.
“Every physician we work with is different,” Gera said. “The motivation is competition amongst each other. ‘How am I doing compared to Dr. Sanders?’ Sometimes the competition is with themselves. Sometimes it’s, ‘How do I adhere to the standards of care?’”
There were also some key financial incentives to switching to in-house analytics. There were unnecessary costs associated with outsourcing, and Signature found that by building the analytics database internally, they weren’t adding to their labor costs. Using developers with a wide range of backgrounds, the system refined its data reporting on a monthly basis during the first year of implementation, simultaneously slashing excess costs and achieving better clinical outcomes.
Signature knew what it had to do. And with a new data approach, now it knew how to do it.
“We knew we had to reduce readmissions,” said Gera. “That’s great, but everyone knows that. That’s like saying, ‘We’re a football team, and we need to score points.’ Well, that’s great, but how? Are we a running team? A great passing team? How do we do what we’re trying to do? We needed to get from a high level down into the details in a way where we didn’t have to customize everything or make it labor intensive, or have weeks and weeks to get the data together.”
Instead, Gera and his team wanted to produce reports containing extreme detail in just five to seven days.
“If the physician says, ‘Well, I had those four readmissions, but what could I do?’, bam, you can say right there, ‘Three of them were avoidable, and this is why.’”
Identifying which readmissions were avoidable has proved a tangible benefit. Many of them, for example, were caused by gastrointestinal hemorrhaging. The medical team reviewed those cases, performed studies, and discovered the majority were likely being generated from the system’s anticoagulant protocols. A tweak to the protocols, and readmissions due to gastrointestinal hemorrhaging were all but eliminated.
“There’s a variety of hooks that kind of get the physicians involved,” said Gera. “You see their gradual engagement with the data getting deeper and deeper.”
Written by Jeff Lagasse. Reprinted from healthcareitnews.com