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Improving Financial Outcomes With Data Analytics

Rene Letourneau, for HealthLeaders Media , August 13, 2013

This article appears in the July/August issue of HealthLeaders magazine.

As healthcare becomes increasingly data-driven, provider organizations find themselves inundated with more information than ever before. Figuring out what to do with all the data may not be easy, but for healthcare finance executives it is a challenge worth tackling because the hospitals and health systems that successfully implement a data analytics program can significantly enhance their economic outcomes and fiscal stability.

The use of data analytics in healthcare is on the rise. Global business consulting firm Frost & Sullivan released a report last year predicting that the adoption of advanced health data analytics in U.S. hospitals would increase from 10% to 50% between 2011 and 2016, a 37.9% compound annual growth rate. Likewise, the February HealthLeaders Media Intelligence Report indicates that 62% of healthcare organizations plan to increase their spending on financial analytics over the next three years; only 3% plan to spend less.

Hospitals in large numbers are being driven to invest in analytics by two factors, says Nancy Fabozzi, connected health principal analyst at Frost & Sullivan, which is headquartered in Mountain View, Calif.

“No. 1 is healthcare reform,” she says. “It’s the fact that there are going to be more patients coming into the system, and they are going to be a different type of patient in the sense that a lot of these people have not been covered before and may not understand how insurance works. They may not fully understand issues like deductibles and copays.”

The second major factor is changing reimbursements, Fabozzi says. “The move away from fee-for-service to value-based payments is a big driver of analytics because it dramatically increases the financial risk … You need to fully understand not just your clinical performance but your operational performance and your financial outcomes. Analytics is at the heart of that.”

With these significant threats to revenue on the horizon, hospitals are faced with the need to maximize their data to find efficiencies wherever possible.

Improving collections

The rapid growth in the use of data analytics in healthcare comes as no surprise to Eric Waller, senior vice president and chief marketing officer at Health Management Associates, a healthcare company based in Naples, Fla., operating 71 healthcare organizations across 15 states with $6 billion in annual net revenue.

Waller says when he joined the organization in 2009, he began looking for opportunities to apply analytics and quickly zeroed in on the revenue cycle as the best place to start.

“Analytics hold enormous potential on the clinical side, but the more immediate opportunities, at least for us, were on the financial side,” Waller says.

“One natural place for us to start was in coding and billing,” he says. “Historically, there have just been a lot of people thrown at the problem. Now, we’ve taken these experts and introduced math and machines, and we’ve seen significant results. We are making sure we are capturing the information and coding properly and getting the revenue we are due. We’ve developed sophisticated models to look for outliers in our coding. The machines crunch the data and identify the outliers.”

Waller says that through the use of data analytics models, HMA is now preventing about $1 million per month in net revenue leakage.

“In a system of our size, if you make small, incremental improvements, the dollars add up quickly,” Waller says. Also, HMA is achieving considerable savings by reducing its reliance on external resources. “We’ve eliminated a lot of the labor costs from outside firms that would normally have people doing manual sampling of files to look for missed codes. We’ve eliminated that expense, which was somewhere between $3 million to $5 million per year.”

“Think about a room full of people just looking through files to make sure the coding is all correct,” he adds. “That’s not very scalable. Just throwing more people at the problem isn’t the answer … We want to identify any areas where we could potentially underbill and also where we could potentially overbill. It’s in everyone’s best interest for it to not be over or under, but for it to be accurate. The most efficient way to do that is with computers and data analytics models.”

Cleveland-based MetroHealth, a 490-staffed-bed health system with $680 million in annual net patient revenue, also uses data analytics to enhance the revenue cycle. The system developed a tool to identify collections patterns and trends in order to predict what the revenue cycle totals will be at the end of every month…. Read Article Here

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This article appears in the July/August issue of HealthLeaders magazine.

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Founder & Head of Data Science Search at Starbridge Partners, LLC.