Case Study: Transforming Uncompensated Care Via Data Analytics

Bad debt cripples healthcare providers, and ever-increasing regulation and governmental scrutiny only serves to exacerbate the problem. But for some, it creates an opportunity to use new technology in innovative ways to transform a constraint into an benefit, not only to patients but also to the provider bottom line.

For James Logsdon, vice president of revenue cycle operations at Texas Health Resources, a chain of 15 hospitals in the Dallas/Fort Worth area, the new regulations and reporting as required under the Patient Protection and Affordable Care Act legislation, rather than prove to be onerous became an opportunity to leverage their data analytic capabilities to create a repeatable business process that “will save money in the revenue cycle, improve patient relations and create a better patient experience.”

In this three-part article, drawn from Logsdon’s presentation at the HFMA Leadership Conference, he describes how his organization employed data analytics to not only fulfill IRS reporting requirements, but also reduce the cost of charity care processing, increase self-pay collections, and  shrink the cost-to-collect ratio of Texas Health’s revenue cycle.

Part 1: The Charity Care Challenge

“We are under pressure to provide more community benefit and more charity,” Logsdon told a packed house at this summer’s HFMA National Institute conference. This is especially important in the world of not-for-profit healthcare where “we need more charity to justify our tax-exempt status.”

Non-profit hospitals must now report all their community benefit activities to the IRS as part of the Schedule H of Form 990. The federal government wants non-profit providers “to report the true community benefit that you’re providing,” says Logsdon. From the government’s perspective, hospitals receive not-for-profit status in exchange for providing community benefits, especially charity care, because “if you didn’t provide that benefit than we would have to.”

For many non-profit healthcare providers, the rubber meets the road in Part III: “Bad Debt, Medicare, & Collection Practices.” Question 3 asks:

“Enter the estimated amount of the organization’s bad debt expense attributable to patients eligible under the organization’s financial assistance policy.”

“That says I want you to start reporting how much of your bad debt may have qualified for charity,” Logsdon says. When he asked the tax expert in his organization exactly what this meant, he was told it was a “put up or shut up question.” As an industry, “non-profits are always complaining that we provide more community benefit than we show,” he says. “So the IRS said, ‘Oh really? Then start reporting it.’”

The next question on Schedule H asks non-profits to “describe the costing methodology used in determining the amounts reported … and rationale for including a portion of bad debt amounts as community benefit.”

Conventional wisdom in healthcare provider revenue cycle circles is that 20 percent to 30 percent of patients who end up in bad debt could have qualified for charity care, but somehow slipped through. Now the IRS wants to know how providers missed these individuals. “Do you not have good science, do you not have good forms, good policies, good procedures, don’t you have a good way to communicate with your patients about your charity policies?” Logsdon says the IRS wants to know.

“It’s kind of a catch-22. How much of your bad debt could have qualified for charity?”

Charity care an expensive process

“I’m not looking for ways to get more charity,” Logsdon says. “I’m looking for ways to collect every single dollar that we can, keep our net days low, improve cash, just like everyone else.”

Furthermore, business processes surrounding charity care are expensive in time, expense, and employee resources. “You probably have staff somewhere that sits in a corner and reviews charity applications all day and they make a lot of determinations based on your internal charity policy,” says Logsdon.

Charity care processing is not always scientific. The process can, at times, be subjective, he says. “I’m sure you make a lot of what I would call ‘judgement calls.’” The intent is to be as objective as possible, “but often times it is a very manual process, very labor intensive, and subjectivity does come in to some of those determinations.”

And more importantly, there is that elusive 30 percent of charity care cases who are missed and end up in bad debt. “I don’t want to spend any more collecting on any accounts I’m not going to get a penny from,” Logsdon says. “If you’re going to spend time and money and human resources collecting from accounts that have zero ability or propensity to pay, you’re just wasting money.” Accounts flow onto bad debt and collections, and what is the recovery rate? “Ours is 3.9 percent of bad debt,” says Logsdon. “Yours may be 2-15 percent, but that means 85 percent you’re not collecting anything.”

Every time a patient account is missed that could qualify for charity, it is a missed opportunity. The solution Texas Health found was, if anything, controversial. Logsdon describes the reaction of his CFO to their proposal: “Let me get this straight? You’re going to start identifying charity before you start collecting and then write them off?”

Part 2: Introducing Presumptive Charity Analytics

Part 3: The Impact of Data Analytics on Charity Care