naraujo100“The 2010 Medicare fee-for-service (FFS) error rate dropped to 10.5 percent in 2009,” according to CMS. “The Medicare FFS error rate is on track for a 50 percent reduction by 2012.”


This is good news, right? Well, it’s a matter of perspective. What’s disturbing is that the number of improper claims still amounts to approximately $34.5 billion. The general public is made to believe that the answer to this lies in the multitude of audits to which CMS and other payer entities are subjecting healthcare providers. Many of us in healthcare would rather we develop a proactive solution rather than “wait” until it’s our turn to be front-page news.


Those of you in this camp, read on for an overview on the areas in your organization’s revenue cycle where errors may occur, along with some basic “how to” clues that will allow you to implement effective solutions.


As all of you are painfully aware, the number and complexity of revenue audits are on the rise. There are MICs, MACs, ZPICs and RACs, just to name a few. What all of these audits have in common is that payers are finding errors healthcare organizations should be identifying and rectifying before claims go out the door.


Revenue Cycle Touch Points


Where to begin? In order to understand how best to use your resources to successfully alleviate at least some of these errors, let’s start by first understanding that there are many touch points along the revenue cycle or patient flow. Within each of these are opportunities for success or potential mistakes that could lead to denials or partial takebacks. These touch points are really occasions during the patient’s stay when there is input or collection of data that eventually impacts the accuracy of submitted claims.


It’s the old adage of “garbage in….garbage out.” The collection of data that is accurate, timely and defensible is what is required to avoid costly audit results.


While there currently are processes in place to collect this data, most organizations do not have what I liken to a “central command post” where it can be reported, validated and filtered to ensure clean claim submission. This “post” is a means to an end in facilitating two-way communication of updated code changes, billing regulations and contract terms, just to name a few factors. It also represents a method to break down silos that currently exist between data collectors at the touch points along the revenue/patient information cycle.


An example of these silos can be seen with Health Information Management (HIM), Contracting and Patient Financial Services (PFS). Each of these areas actively affects the data utilized for claims submission and approval, yet they usually do not share or compare information. When a claim is denied, how often does your PFS department contact HIM or contracting to inform them and evaluate if perhaps there was a contract carveout or a missing fifth digit, for example?  Enacting the “command post” model allows this information to be housed in one central location where filters can be applied to the data to ensure the charge master possesses current codes and to guarantee that contract terms are considered and possible problems are communicated back to the originator of the data collection for validation and correction.


All of the departments charged with data collection along the patient/revenue cycle are working with less staff and greater demands. The constantly changing regulations and complexity of updates often are more than they can keep up with. As such, it is time to embrace the technology that is now available to automate this process in a fashion in which we “push” data out to facilitate human interaction rather than rely on already busy professionals to “pull” the data in.


By utilizing one of the several cost-effective data collections tools available to create a concurrent data file that continuously is updated and shared along the patient/revenue cycle, information can be shared, pushed AND monitored by the “command post.” Ideally, a “commander” who oversees timely electronic file updates of ICD-9 codes, contract terms, insurance statuses and other relevant data impacting clean claim submission mans this automated tool.


This same person would be the one to push problems back to one of the revenue/patient touch points for clarification prior to claims submission and eventually to distribute claims payment results back to any and all necessary areas if a claims denial or partial payment is all that is achieved.


Go Offensive


It’s time to go on the offensive! The process utilized by payers to perform audit targeting is not magic.  We have all of the information we need, even if it is not necessarily readily available in an organized format. By developing a central hub of information you can begin to walk through the patient/revenue cycle and identify opportunities for improvement and by automating the process, and even can begin to perform the same kind of data-mining currently performed by the auditors targeting our mistakes. Remember, the best defense is a well-informed offense.


About the Author


Ms. Araujo received her degree in health information administration from Loma Linda University. She has extensive experience in management of organizational change projects with an emphasis on best practices with a fiscal focus. Currently Ms. Araujo is Vice President, Sales and Consulting Services for the national firm SOURCECORP, focused on their healthcare division, SOURCECORP HealthSERVE.



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