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HPA Harnesses the Power of "Big Data" to Generate Big Savings in Healthcare Spending

Health Mason Robotic Payment Processing Solution Automatically Analyzes Gigabytes of Provider/Payer Data to Catch Errors, Stop Insurance Providers from Paying Erroneous Claims that Cost Billions Each Year


News provided by

Healthcare Productivity Automation

Nov 01, 2011, 09:00 ET

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FRANKLIN, Tenn., Nov. 1, 2011 /PRNewswire/ -- Healthcare Productivity Automation (HPA), provider of advanced healthcare workflow automation solutions, is leading the charge in the healthcare industry to harness the power of "big data" to reduce the cost of health care. By automatically and continually analyzing gigabytes of claims data in real time—as it is processed—the company's Health Mason robotic payment processing solution can spot anomalies and detect even the smallest of errors, saving health plans and hospitals big bucks.

The Problem of Errors

Amid the raging debate over healthcare reform, there's little dispute that making health care more affordable is a crucial part of the solution. But, in searching for ways to cut costs without compromising care, many in the industry overlook billing errors as "small potatoes" and consider them to be a necessary, if unfortunate, part of the system.

"A $5 error here or $15 mistake there may not seem like much of a problem—and frankly, they often cost more to fix," said HPA CEO Sal Novin. "But, when that same $5 or $15 error is repeated thousands of times a week, the costs really start to add up."

In fact, in fiscal year 2010, Medicare and Medicaid alone made more than $70 billion in improper payments to medical providers, not to mention the staggering cost of erroneous payments made by private insurers.  

Setting aside blatant fraud, most bona fide billing errors are the result of simple human error—manual processing slip-ups that occur when rules are incorrectly or inconsistently applied. Certainly automating the process can eliminate these human errors from the equation. But, in cases where the process itself contains errors, "you want to absolutely avoid automating a bad process and that's where the value of big data shines," Novin said.

"Our solutions can analyze the process itself. We go beyond saving on labor costs by automating the process to actually improve the quality of the process itself to achieve consistent and accurate payment," he said. "This is where big data comes into play. Health Mason can continuously monitor massive amounts of data generated to spot those needle-in-a-haystack errors that, when aggregated and accumulated over time, cost enormous amounts of money, most of which you don't even realize is going out the door if you're processing manually."

Big Data, Big Savings

Part of the challenge in correcting payment mistakes on a broad scale is the notion that the enormous amounts of data being generated make it impossible to analyze using traditional methods. In the case of claim errors, a periodic audit simply isn't going to catch the type of random errors that occur more frequently than providers and payers may like to admit.

But, by gathering and correlating these massive data sets—aka "big data"—through automation with Health Mason, the problem quickly comes to light. In fact, a recent McKinsey Global Institute report on big data suggests the U.S. health care sector could create more than $300 billion per year in added value, two-thirds of it in the form of reducing expenditures by about eight percent, through the creative and effective use of big data to drive efficiency and quality.

Big Data in Practice

"You can think of big data as a way of magnifying small problems," Novin said. For example, a $200 payment error that occurs in 1 out of 100 durable medical equipment (DME) claims will show up 50 times in a month where 5,000 DME claims are filed. "But, if you analyze a year's worth of data, the error will show up 600 times and as a $120,000 error," Novin said. "With Health Mason in place, once errors are detected we can track the problem down to the exact days and times the errors took place and find the root cause."  

The sensitivity to anomalies can sometimes be astonishing, making a tiny error stick out like a sore thumb. In one instance, Health Mason detected a payment error that occurred every week on the same day. For years, the error had gone unnoticed because it was invisible to conventional auditing procedures and reports. Health Mason pinpointed the error to a specific provider who was incorrectly billing a specific modifier, on a specific claim type, on a specific day. Like most payment errors, it turned out to be an honest mistake: A doctor's office had hired a temp to work one day a week. The temp had used a cheat-sheet that was perfectly correct except for one small mistake. The total annual cost of that error was unimpressive; however, the cumulative impact of these small errors is enormous.  

"Similar scenarios take place every day all across the country, and it's easy to see how these seemingly minor inconsistencies add up to massive costs," Novin said. "Using automated tools to analyze the data gives us incredible acuity to detect and correct these errors that would otherwise continue to drain dollars from the system—dollars that could be invested in more innovative treatments, enhancements in IT and all of the other areas where our healthcare system could use it to improve patient outcomes."

Collecting Quality Data

A key ingredient of big data is the aggregation of high-quality and high-value data. Health Mason tracks data consistently and aggregates it in any format – making reporting fast and simple. Health Mason has been used in this manner to validate numbers reported by other systems.  In one instance, Health Mason found exceptions in identified savings from a code review vendor. The health plan was required to pay only for realized savings,  but was being billed for all identified savings. "In many cases you don't have to think of tracking a data point in advance because it's already being tracked," Novin said.

Novin says these are just a few of the ways that automation and big data can move us closer to a more affordable healthcare system. Healthcare administration costs amount to one-fifth of total U.S. spending on health care, to the tune of some $300 billion a year. By finding ways to automate the system, Novin says the savings could be tremendous.

"We're sitting on massive data sets that present an enormous level of correlation possibilities," he said. "Just like the gold rush, everyone's out looking for the mother lode of savings—the one big hit that's the answer—but  the reality is that, much like gold, the savings  are in tiny nuggets that must be extracted. We have the tools to mine this data to find incredible savings and improve efficiency and performance of the process."

For more information about HPA's Health Mason cloud-based automated robotic workflow platform, visit www.hpapro.com.

About HPA (Healthcare Productivity Automation)

Based in Nashville, Tenn., HPA is a healthcare-focused software development and consulting firm specializing in helping payers and providers save money through the automation of manual processes. Its flagship Health Mason family of SaaS solutions improves the provider-payer payment relationship by automating claim and payment management processes, reducing costs while improving quality and achieving more consistent processing. Used by some of the country's major healthcare insurance companies and service providers, HPA solutions received the 2009 Nashville Technology Council's Innovator of the Year Award. To learn more visit www.hpapro.com.

SOURCE Healthcare Productivity Automation

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