Revenue Leakage: How Big Data Can Address Challenging Denials at Academic Medical Centers

It’s no secret that many hospitals find themselves in faltering fiscal health lately. According to the Harvard Business Review, since the start of 2016, some of the nation’s top hospitals have lost hundreds of millions of dollars of income.

These challenges can be especially pressing for academic medical centers (AMCs), who process a large volume of complex, high-ticket medical claims and generate revenue from direct patient care.

Today, AMCs are finding themselves less insulated from changes in the healthcare consumer patterns that are causing revenue leakage. For instance, patients overall are visiting hospitals less and stays are also much shorter than historic averages. As reported by the New York Times, in 1980, the average stay was 7.3 days; in 2015, the figure was 4.5 days. This is good news for patients, but not for a hospital’s bottom line. Even AMCs, who receive additional funding like government subsidies, grants, investment income, and charitable donations, are now feeling the pinch.

In such a climate, having the right tools to recover revenue previously lost to denials can make a huge difference. While recovering earned revenue is of utmost importance to keep a hospital afloat, it can become an afterthought for some providers to capture the hardest-to-reach revenue, as they must weigh getting bills out the door against evaluating how they have or have not been paid. Two factors are changing this. One is that the economic environment no longer allows for being sanguine about challenging denials. The other is that big data and artificial intelligence are helping hospitals better identify such opportunities. 

AMCs fight against lost revenue 

Revenue leakage — the inability to collect earned revenue — is a significant, pervasive challenge facing today’s teaching hospitals. Such AMCs represent only 5 percent of America’s hospitals, according to the Association of American Medical Colleges (AAMC). But those 400 or so major teaching hospitals and health systems in the U.S. provide nearly 25 percent of all hospital care, including 25 percent of all Medicare inpatient visits, 24 percent of all Medicaid inpatient visits and nearly 40 percent of the nation’s charity care, making them especially vulnerable to at-risk revenue streams.

The tightening of already-narrow margins makes uncompensated care a topic of great concern and constant conversation among teaching hospital executives and boards. In a recent fact sheet from the American Hospital Associations (AHA), despite Medicaid expansion, in 2016 uncompensated care increased by $2.6 billion (7 percent) to $38.3 billion, the first annual increase since 2013.

Can big data help? 

Happily, the emergence of this revenue shortfall has coincided with the growth of big data and the maturation of computing systems that are able to analyze data effectively. By leveraging big data and analytics, such discovery tools can alert AMCs to newfound opportunities to collect and address revenue leakage quickly and easily. In particular, they can identify hard-to-find insurance coverage and incorrect policy numbers; manage timing delays and changes in payer eligibility databases; identify the correct payer information for a specific service; and address unique Medicare billing challenges, among other methods.

Analytics-based technology can also identify Medicare account underpayments and billing system and process breakdowns resulting in unreceived, unaccepted, returned or denied claims — all of which can result in uncompensated care or underpayments.  

Such systems enable already-strained finance and operations departments at AMCs to shift employee attention to other value-added activities and automate what has historically been a very time-consuming and manual billing process.

Big data’s potentially game-changing impact

Big data can potentially transform the healthcare industry. Such data, when employed with artificial intelligence systems, can predict epidemics and find new cures by pooling the world’s knowledge and analyzing the data for potential solutions. In addition, wearable devices and electronic medical records can shift the focus from reactionary care to preventative care.

Behind the scenes though, such technology can also help hospitals leverage patient data to better manage their revenue cycles. That helps them control costs, improve profits and cut down on lost revenue and wasted overhead. Through the use of big data technologies, hospitals and other healthcare facilities have been able to reduce costs by more than 10 percent and grow revenue by 30 percent.1

As hospitals and AMCs face increasing trouble making ends meet, big data may have a similarly far-reaching effect on the healthcare landscape.  

————————————————————————–

About the author

Todd Langer, VP of TransUnion Healthcare Ops, has a B.S. in accounting from Brooklyn College and a J.D. from Brooklyn Law School. He is certified by HFMA in patient accounts and managed care and has more than 40 years of experience in Healthcare billing, finance, and administration.