How Intelligent Verification is Disrupting the Status Quo of Claims Processing
Ever wonder why you’re losing revenue due to claim rejection, denials, missed deadlines, etc. especially when you either contract with a clearinghouse or with a 3rd party provider/solution to minimize this very issue?
Before leaping into that discussion, lets define a few terms:
Automated Real-Time Intelligent Verification is a process used to provide additional depth of revenue recovery and operational effectiveness across healthcare sectors such as Labs, Hospitals, Urgent Care, Ambulance Services, Revenue Cycle Management companies and many more.
Charge scrubbers are software solutions used to identify billing and medical coding issues and is generally done prior to creating a claim.
Claim scrubbers are also software solutions used to identify medical coding and billing issues and takes place after a claim is created prior to submission to the payor.
Provider Collected Data is the raw data/information received from patients, orders, encounters and requisitions prior to submission into a scrubber.
First-pass ratios typically refer to the ratio of claims that make it through clearinghouse edits and are passed on to payers however payment is not guaranteed.
Clean claim is one that has no defects or impropriety, including but not limited to, omissions, substantiating documentation or anything that otherwise would prevent a timely payment, and has never previously been submitted and/or rejected for any reason.
Eligibility Benefit Inquiry is defined by CMS as an eligibility/benefit inquiry transaction used to obtain information about a benefit plan for an enrollee, including information on eligibility and coverage under that health plan.
Claim rejection is a claim submitted to a clearing house but is not forwarded/processed and sent off to the insurance company and/or payor, due to incorrect or missing information.
Claim denial is a claim that has been processed and sent onto the respective payor but is deemed unpayable for a few different reasons, i.e., missing information, incorrect codes and duplication.
CCR (Clean Claim Ratio) is defined by HFMA in its MAP keys program, only clean claims should be used to calculate clean claim ratios. “CCR is calculated by dividing the number of claims that pass all edits, thus requiring no manual intervention, by the total number of claims accepted into the claims processing tool for billing. (Jan 2018)” Remember however, claims accepted into a claims processing tool are generally run through a claim scrubber and for those claims that make it through the claims scrubber without intervention are those being referred to here.
Automated Real-time Intelligent Verification is taking the industry by storm and creating a new way for healthcare providers to improve their bottom line. For years and still true today, many healthcare hospitals, laboratories, physician providers, pharmacies, rely on clearing houses and 3rd party software solutions such as claim scrubbers, charge scrubbers, eligibility benefit inquiry tools, also known as an eligibility checkers, to manage the billing side of the revenue cycle and claims processing side of the business. For many, this is just the way it’s always been done and have come to accept there will be a certain number of rejections, denials and write-offs that will occur.
While there is value in the use of clearinghouse’s, claim scrubber’s and charge scrubbers, they don’t solve everything. Many clearinghouses and claim scrubbers offer eligibility as a feature and almost all are simplistic in nature. On the surface, the First Pass Ratio appears to be acceptable because they made it through the initial edits. However, having information in a required field may get you through an initial edit but having the correct information in every field will yield you a higher return. Charge and Claim scrubbers can clearly help as they’re used to identify coding and billing issues, but unfortunately in both cases are both being done late in the overall process and only offer eligibility as a feature which is not part of their core business.
This can be further demonstrated by simply calculating the clean claim ratio. However, many organizations define this quite differently. Todd Andros, founder of tevixMD says, “you must eliminate the noise when quantifying how well your 3rd party system is, or in some cases, is not working for you.” Some 3rd party organizations run all claims through a claim scrubber prior to submission to the payor. When they define their clean claim ratio some calculate this on the number of clean claims the claim scrubber yielded vs. the number of those claims that were then rejected by the payor. So, what happened to all the original provider collected data that went into the claim scrubber and got stuck? Don’t get caught in this trap. The only way to really know how well your solution is or is not working is to identify the ratio of the actual input file/Provider Collected Data in its totality vs. the results rendered prior to and after claim submission, i.e., Claim Rejection.
This brings us back to the first part of the real problem and that’s Verifying the Identity of the patient. Obtaining provider collected data irrespective of its origin and, getting accurate demographic information is challenging. Making errors and omissions during registration or providing a wrong address to lacking prior authorization can cause an insurer to reject and deny a claim. Many institutions try to resolve this through a UPI (Unique Patient Identifier) which is only useful if the patient stays within that health system.
How many times are patients not identified correctly, either from a paper requisition, during the Assession process and/or incomplete information from a provider order, or their name is simply documented differently upon registration? Patient information, irrespective of where it came from, should be validated in real-time from a Global Patient Index for each date of service (DOS). Once this is achieved and only at this point can a true match to a patient’s eligibility status occur. The best place for this to be incorporated in the overall revenue cycle process is up front at the very start of the process beginning with an initial encounter, order or requisition and the shift in making this change is underway by utilizing Intelligent Verification as part of the overall process. GPI also known as MPI (master patient index) has to do with grouping orders/claims under one master patient identifier.
The second part of the real problem is Insurance Eligibility. It is increasingly difficult for providers and revenue cycle companies to wade through all the insurance plans, the IPA’s, (Independent Private Associations) as well as the different products offered by each one. In addition, the introduction of high deductible health plans resulted in the patient now becoming the largest payor. These factors alone make it difficult for healthcare providers to meet the time limit for claim submission and/or re-submission as well as reducing rejections and denials. Providers ultimately end up absorbing the re-work cost and accept the fact they will incur write-offs. Once a patient’s identity is verified, their active insurance plan must be accurately validated. This isn’t always simple to do especially when, a patients’ information may not match the information they have on file with their insurance plan. Also, some insurance providers run exclusive provider programs, which means their policies may only cover hospitals, clinics, and treatment in their defined network/in-network. For those without this level of visibility for in and/or out of network eligibility may find a particular type of care rejected by the patients’ health plan.
Other nuances such as validating whether the plan covers certain medical expenses, does it require pre-authorization or is it a dental plan or vision plan only, add further complexities to this process. Identifying, managing, and avoiding denials is necessary to protect revenue and reduce write-offs. Patented algorithms which exist as part of a Real-time Automated Intelligent Verification Solution clearly place healthcare providers back in the driver seat controlling their own outcome.
For some, the value of simply rectifying the patient identity and eligibility problem may seem negligible but let’s take a moment to do the math. According to the MGMA, the average cost to re-work a claim that has been rejected or denied is about $25 for each claim. Calculating this based on the number of claims that require re-work each month, for example, would mean that100 claims @ $25 would cost a practice an estimated $30K/yr. Now of course there are many reasons for rejections and denials but according to the MGMA and Change Healthcare’s 2020 Revenue Cycle Denials Index, one of the top reasons for denials is due to registration and eligibility. In fact, they found this number to be nearly 27% which demonstrates the need for greater intelligence and automation into the front end of the revenue cycle.
Only by disrupting the status quo of revenue collection with Automated and Real-time Intelligent Verification process can this begin. Employing this process assures and gives you the confidence that the percent of rejections, and denials will not be because of the lack of accurate patient demographic, insurance eligibility, and/or Medicare/Medicaid. As many organizations fight to expand their offerings in the quest for additional business and ultimately improve their bottom line, sometimes the buyer/user of 3rd party software solutions and their specific needs and workflow requirements are often overlooked. There are times to capitalize on “single solution” vs, “best of breed” but if your one solution doesn’t incorporate best of breed, like Automated Real-time Intelligent Verification, you could find yourself eliminating the very solution that could drive real revenue to your bottom line.
By Margaret Nash
Vice President of Business Development, tevixMD