Analytics helping Mercy Health get operational costs in line

By | February 18, 2019

Mercy Health in Springfield, Mo., conducted data analytics to better understand the costs of its procedures and what affects them.

For example, it sought to understand which doctors repair a knee for $ 10,000, while others do the same procedure for $ 4,000.

The facility faces a problem that is by no means unique in healthcare—every healthcare system is experiencing declining reimbursement, but it’s hoping to be incentivized for improving quality of care.

“Our goal is to reach a 4 percent operating margin, so we looked for the greatest costs—perioperative, nursing, labor and pharmacy,” says Curtis Dudley, vice president of enterprise analytics data services and performance consulting at Mercy Health, a 19-hospital delivery system across parts of seven states.

Analyzing data from the electronic records system enables Mercy to give physicians evidence of best practices clinically and financially, Dudley explained during an educational session at HIMSS19.

The health system contracted with SAP and implemented its HANA business intelligence and analytics tools and soon learned that a robust technology infrastructure matters, Dudley acknowledged.

HANA was able to load 40 million rows of data and drill down to individual doctors, types of implant they are using and other items being used by physicians in the organization.

“We would have a meeting and I couldn’t answer a question, so I had to do research then have another meeting, and now I don’t need the other meeting because HANA makes all my analytics faster and cuts my data modeling time in half,” Dudley said.

The cost analyses included findings that surprised physicians, particularly one of the highest-cost physicians who regularly used a special cauterizing tip that cost twice as much as other doctors’ tips, but he didn’t know that and switched tips when he learned of the cost.

Now, with real-world evidence from analytics Mercy Health Springfield is working with manufacturers to measure the performance of medical devices using data sets from the EHR.

Big savings can come from anywhere in a healthcare enterprise, Dudley stressed. For example, why are some doctors using cement bowls for plastering while others use a cheaper bowl?

“We want to understand what devices are of a high quality and lower cost, and we want peers to know the wealth of improvement that can be achieved from the opportunities of data,” he concluded.

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