For the savvy CFO, VP, or administrator looking to reduce or eliminate denials at their root, thereby markedly improving the organization's cash flow, this white paper introduces the methodology to do that immediately by quickly and easily using the big data presently on hand and available.
The capture, storage, and application of data towards the generation of measurable value in the healthcare environment are paramount. All healthcare entities that see patients are already capturing and storing this data. The buzzword for this collection of information is “Big Data”. There seems to be no shortage of articles, blogs, white papers, etc., underscoring the importance of forward-thinking enterprises. Most point to a necessity for the prioritization of major expenditures, whether for software and systems or personnel, to be able to make use of big data in a way that yields the desired value.
Big data is often pointed to as the future of business. Said to be poised to change life as we know it, we all contribute to the body of data collectively recognized as “Big Data”, and healthcare is no exception to that. With virtually every healthcare entity creating and storing volumes of usable information, big data stands to impact the industry unlike anything else to date, especially in the areas of meaningful use, quality outcomes, and population health. Of equal or greater value is the potential for big data to boost revenue cycle performance and cash flow of hospitals, health systems, and physician practices.
But what exactly is “Big Data”? Information is said to be part of and contribute to big data if it has five specific characteristics—volume, variety, velocity,
veracity, and value.
In the revenue cycle management process, the focus of this paper, the value of the data and
resulting opportunity is actually increased realized income, as opposed to just cost savings and waste reduction, which is typically where the majority of value is seen in healthcare information.
The Size of the Problem
“The reimbursement challenges ahead to get paid may require several new RCM applications, and the blunt realities that Black Book warned of from the 2014 surveys are showing signs of occurring…
failing RCM systems will close marginally performing hospitals for good and will get CFOs fired,” warns Doug Brown, Managing Partner of Black Book.
Seemingly contrary to that warning, denial rates have declined in recent years, largely due to automation and advancements in revenue cycle technologies. Yet, the best performing organizations are still reported to have denial rates slightly below 5%. More average performers accept denial rates in the 5-10% range, and poorer performing healthcare organizations’ denial rates exceed 10%. According to a report published by the IRS, the average total revenue for hospitals in the U.S. in 2012 was $179 million, which means that even the best performing organizations average nearly $9 million in denials annually. The dollar value attached to denials for more marginal performers could be double that figure or greater.
With millions of dollars at stake, especially in the face of shrinking margins and declining reimbursement, recouping as much of that amount as possible is important although, that, too, comes at a cost. The commonly-accepted dollar metric for denial rework is $15 per denial, which further compounds the denial management challenge and leads many organizations to abandon the pursuit of denials altogether. The greater opportunity here is reducing or eliminating denials permanently at their cause.
The opportunity to harvest and examine denial data to reveal key issues that can be translated into actionable items is available now, regardless of the number of disparate systems used. Simply put, the variety, sophistication, and accessibility of big data are transforming denial management, allowing administrators and physicians to view their performance on a granular level and to respond with action that resolves denials permanently at their root. Big data analytics, the process of examining big data to uncover hidden patterns, unforeseen correlations, and other actionable information, can make clinical operations more profitable, decision-making more informed, and management more results-focused by utilizing claims and remittance data to create predictive and prescriptive models.
To accomplish this, you must first recognize and embrace the opportunities technology provides. With so much emphasis placed on implementing and incorporating technology into the clinical space in recent years—be it by government mandate, insurance carrier requirements, or corporate strategic priorities—the necessary infrastructure and data gathering framework is in place and used daily.
A commonly accepted financial methodology focuses on reporting on gross receipts—what income is expected—upon which income projections and planning are based. However, not given nearly as much attention are the pitfalls and snags along the way that diminishes receipt on those charges. This approach of using your data as a vital additional ingredient of the analysis and subsequent reporting does just that, enabling transformative denial management impacting both ends and the bottom line.
Historically, business offices have looked at charges/denials as individual events to be managed independently of other similar events. By analyzing the data on hand, however, a broader view can be taken, facilitating the detection of larger trends, commonalities, and issues represented by the individual types of denials, allowing assignment of protocols and fixes with predictive, widespread results. This shift positively affects denials, yielding an exponential impact in the categorical reduction or elimination thereof.